JRC (2009) - Plug-In Hybrid and Battery-Electric Vehicles

Plug-in Hybrid and Battery-Electric Vehicles: State of the research and development and comparative analysis of energy and cost efficiency Françoise Nemry, Guillaume Leduc, Almudena Muñoz

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JRC 54699 Technical Note

Luxembourg: Office for Official Publications of the European Communities  © European Communities, 2009 Reproduction is authorised provided the source is acknowledged

Plug-in Hybrid and Battery-Electric Vehicles: State of the research and development and comparative analysis of energy and cost efficiency

F. Nemry, G. Leduc, A. Muñoz

JRC Technical Notes

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1 Table of contents 1 2 3

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Table of contents ...................................................... ........................................................................................................................ ...................................................................... .... 2 Introduction .................................................................... ................................................................................................................................. ................................................................ ... 4 Technological components .................................................................... ............................................................................................................. ......................................... 4 3.1 General definitions....................................................................................................... definitions................................................................................................................. .......... 4 3.2 Power train architecture ............................................................ ......................................................................................................... ............................................. 5 3.3 Energy management................................................... management............................................................................................................... ............................................................ 6 3.3.1 Advantages and disadvantages of PHEVs......................................................................... 8 3.4 Batteries .................................................................. .............................................................................................................................. ............................................................... ... 8 3.4.1 Key parameters ............................................................... .................................................................................................................. ................................................... 8 3.4.2 State of the art and anticipated developments ............................................... ................................................................. .................. 10 3.4.3 Battery characteristics.............................................................. characteristics...................................................................................................... ........................................ 13 Tank-to-wheel energy energy performance.............................................................................................. performance.............................................................................................. 15 4.1 Introduction............................................................................................... Introduction.......................................................................................................................... ........................... 15 4.2 Literature review .......................................................... .................................................................................................................. ........................................................ 16 4.3 How to measure the final energy consumption consumption of PHEVs?................................................. 19 4.4 Energy performance performance of EDVs: first estimations ................................................ .................................................................. .................. 22 4.4.1 Reference cars energy performance and cost .......................................................... .................................................................. ........ 22 4.4.2 Battery specifications ............................................................ ...................................................................................................... .......................................... 23 4.4.3 Energy efficiency...................................................................................... efficiency............................................................................................................. ....................... 23 4.5  Need for further work ....................................................... .......................................................................................................... ................................................... 25 Vehicle costs.......................................................................................................... costs................................................................................................................................. ....................... 26 5.1 Literature review .......................................................... .................................................................................................................. ........................................................ 26 5.2 Vehicle cost comparison for the EU ........................................................... .................................................................................... ......................... 27 5.3  Need for further work ....................................................... .......................................................................................................... ................................................... 28 Battery charging options and and infrastructures................................................................................ 29 6.1 Introduction............................................................................................... Introduction.......................................................................................................................... ........................... 29 6.2 Battery charging options .............................................................. ...................................................................................................... ........................................ 29 6.3 Expected recharging time and implied charging infrastructure ........................................... 31 6.4  Need for further work ....................................................... .......................................................................................................... ................................................... 32 Impacts on, and role of electricity grid operators operators ........................................................... ......................................................................... .............. 33 7.1 Introduction............................................................................................... Introduction.......................................................................................................................... ........................... 33 7.2 From mono-directional mono-directional to bi-directional power flow management ..................................... 34 7.3  Need for further work ....................................................... .......................................................................................................... ................................................... 36 References ............................................................... .................................................................................................................................... ..................................................................... 37

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Acknowledgement The authors of this paper would like to thank Christian Thiel (JRC/IE Institute), Adolfo Perujo and Biagio Ciuffo (JRC/IES Institute) for their suggestions on the draft version.

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2 Introduction Electric-drive vehicles (EDVs) have gained attention, especially in the context of growing concerns about global warming and energy security aspects associated with road transport. The main characteristic of EDVs is that the torque is supplied to the wheels by an electric motor that is powered either solely by a battery or in combination with an internal combustion engine. This covers hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), and  plug-in hybrid electric vehicles (PHEVs), but also photovoltaic electric vehicles (PVEVs) and fuel cell vehicles (FCVs). As part of its transport and energy modelling activity, IPTS initiated research work with a view to assess the economic and environmental impacts for the EU27 of a future market  penetration of those car technologies, with a focus on BEVs and PHEVs. As a starting step, IPTS reviewed the literature and prepared this report which provides a summary description of the technology aspects, the current state of the research and development in the field. It also elaborates consistent sets of data about the vehicle technologies in view of the subsequent modelling work to undertake the assessment. The report also identifies a series of areas where more data and assessment are needed. This report also represents a first IPTS contribution to a JRC horizontal project involving IE and IES.

3 Technological components 3.1

General definitions

To be more precise, the following definitions are used this report:

Battery Electric Vehicles refer to vehicles propelled solely by electric motors. The source of   power stems from the chemical energy stored in battery packs which can be recharged on the electricity grid. The future of such vehicles strongly depends on the battery developments (performance and cost). Plug-in Hybrid Electric Vehicles refer to vehicles that can use, independently or not, fuel and electricity, both of them rechargeable from external sources. PHEVs can be seen as an intermediate technology between BEVs and HEVs. It can indeed be considered as either a BEV supplemented with an internal combustion engine (ICE) to increase the driving range, or  as a conventional HEV where the all-electric range is extended as a result of larger battery  packs that can be recharged from the grid. As an example, the IEEE1 (board of directors, 2007) defines a PHEV as ''any hybrid electric vehicle which contains at least: (1) a battery storage system of 4 kWh or more, used to power  the motion of the vehicle; (2) a means of recharging that battery system from an external 1

http://www.ieeeusa.com/policy/POSITIONS/PHEV0607.pdf 

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source of electricity; and (3) an ability to drive at least ten miles in all-electric mode, and  consume no gasoline. These are distinguished from hybrid cars mass-marketed today, which do not use any electricity from the grid .'' 

A large range of options are currently developed that vary in terms of power train architecture, energy mode management, battery type, that can influence the energy  performance and costs.

3.2

Power train architecture

A plug-in hybrid electric vehicle can be designed with the same types of technological architecture as current hybrid vehicles, namely series-hybrid, parallel-hybrid, or combined series-parallel hybrid (split): •

Series-Hybrid: this configuration is to be associated with electric cars since only the electric motor provides power to drive the wheels. Sources of electrical energy are either the battery pack (or ultra capacitors) or a generator powered by a thermal engine. An example of PHEV series is the famous Chevrolet Volt developed by General Motors2. Such vehicles are also called Extended-Range Electric Vehicles.

•

Parallel-Hybrid: in this case, both the electric motor and thermal engine can provide  power in parallel to the same transmission.

•

Power split or series/parallel hybrid: this configuration combines the advantages of    both parallel and series hybrid concepts. This is for instance the architecture implemented in the Toyota Prius model (Hybrid Synergy Drive). This relatively complex architecture allows running the vehicle in an optimal way by using the electric motors only, or both the ICE and the electric motors together, depending on the driving conditions.

Figure 1 provides an illustration of the PHEV configuration. PHEV

HEV Regenerative braking

FUEL

ELECTRICITY GRID

B A T T E R R II E E S S

Generator 

ICE

ELECTRIC MOTOR

D RI V E T RA IN

Figure 1: Simplified representation of HEV/PHEV configuration (blue: series; red: parallel) 2

See also its EU version Opel Ampera.

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3.3 Energy management  When driven, the BEV and PHEV State of Charge (SOC) – i.e. the fraction of total energy capacity remaining in the battery - varies within a certain window, given by the difference   between maximum and minimum SOC. The technological advantage of PHEVs stems from its capability of driving on different energy modes, resulting in different SOC levels. Two  basic modes are possible (see e.g. [Market and Simpson, 2006] and [EERE, 2007]): •

In the Charge Depleting operating mode (CD), the vehicle is powered only or  almost only by the energy stored in the battery, and the battery's SOC gradually decreases up to a minimum level (which depends on the battery size). The vehicle thus mostly behaves as an electric car, which particularly suits to urban driving [Shiau et al., 2009]. This mode can actually operate in two ways: under the "CD blended mode", the ICE is turned on. Under the "CD all electric' mode", the ICE is turned off.

•

During the Charge sustaining mode (CS), the SOC over a driving profile may increase and decrease but will, on the average, remain at its initial level. The battery's SOC is maintained within an operating range and can be recharged through regenerative braking and from the ICE. In this case, PHEVs behaves as conventional HEVs.

Depending on the driving conditions, the two modes can be combined over the distance travelled in such a way as to reap the full advantage of the PHEV and extend the driving range. This is illustrated in Figure 2. The resulting discharge cycle will influence the total energy demand over the distance travelled and the environmental performance. In practice, the feasible combination will depend on how often and where the driver could charge his vehicle from the grid, on the driving cycles, etc. However, at some point the vehicle needs to rely on fuel to extend the driving range and then switches to the so-called 'Charge Sustaining' CS mode.

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Figure 2: Example of discharge cycles for BEVs, HEVs and PHEVs Source: [Anderson, 2008]

PHEVs are differentiated according to their All-electric range (AER) i.e. the distance driven electrically up to the point at which the ICE engine first turns on. It can be also defined as the distance travelled before the vehicle switches from charge-depleting to charge-sustaining operation [Gonder and Simpson, 2007]. This is measured for a reference driving cycle, usually on urban driving cycle. The notation "PHEVx" is commonly used to specify the PHEVs AER. For instance a PHEV30 corresponds to a PHEV with a 30 miles electric range. Typical PHEVs AER are in the range 20-60 miles. The PHEVx notation is more indicative for the case where, in practice, a PHEV would operate on all-electric CD mode over the first x kilometres, and after in CS mode3. But this definition is less appropriate if a PHEV operating in CD blended mode for which both electricity and gasoline are used to power the vehicle. In this case, it would be more convenient to define the suffix x as the equivalent distance of petroleum-based fuel displaced  by electricity from the battery [Gonder and Simpson, 2007]. It has also to be noted that, in practice, the real world driving behaviour and energy management mode will influence the actual driven distance. Therefore, a given AER doesn't mean that the vehicle may or may not actually drive the corresponding distance electrically.

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This is the case for instance of the Chevrolet Volt (hybrid series) whose the ICE is used as backup source of energy to provide onboard electricity when the batteries reach their lower bound limit SOC.

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3.3.1 Advantages and disadvantages of PHEVs Figure 3 summarises the main advantages/disadvantages associated with PHEVs. These elements are analysed in the present report, with a special focus on fuel efficiency (section 4) and costs (section 5). PHEVs

+

Ability to run on Charge Depleting (as for BEVs) or Charge Sustaining mode (as for HEVs)

Fuel consumption/GHG emissions depends on many parameters (e.g. driving and charging patterns, AER, CD mode management, efficiency in the CS mode)

Grid connection capability Extended All-Electric Range (typically up to 60 km) can displace important quantities of fuel

Market penetration greatly depends on battery developments (performances and costs)

GHG emissions are generally r educed (depending on the electricity generation mix = f (space, time))

Additional weight (battery pack, etc.)

Driving range not limited as for BEVs Higher initial costs

Take advantages from HEV and BEV driving performances

Impacts on the electricity grid need to be carefully assessed

Can greatly improve local air quality V2G capability

Infrastructure costs (charging facilities, etc.)

Well suited to urban areas

Figure 3: Pros and Cons of PHEVs  Note: some of the negative aspects of PHEVs vs. HEVs would be positive vs. BEVs (e.g. costs, battery weight etc.)

3.4

Batteries

Battery performance and cost are essential factors for the development of electric vehicles. The present chapter provides a brief description of current progress and potential evolution of  the different aspects concerned.

3.4.1 Key parameters Batteries design variables include (see e.g. [Axsen, 2008; Anderson, 2008; Anderson, 2009]):

Energy The energy storage capacity (kWh) is of high importance since it will directly determine the distance the vehicle can drive on the CD mode, as well as the mass of the battery pack. For  PHEVs, the energy storage requirement considered in the literature typically varies from ~6 8

kWh to 30 kWh depending on the CD range (compared to 1-2 kWh for conventional hybrids and 30-50 kWh for BEVs). The energy storage capacity represents the 'available' or 'total' energy capacity depending on whether the SOC window is taken into account or not (e.g. a 10 kWh of total energy capacity operating with a 65% charge swing would have only 6.5 kWh of  available energy). Generally, the battery usable energy increases linearly with the CD range [Rousseau et al., 2007]. Both high specific energy (Wh/kg) and energy density (Wh/l) – i.e. the ratio of the total energy (Wh) to the battery mass (kg)/volume (l) – is crucial to achieve high energy storage capacity without entailing significant additional mass/volume.

Power The peak battery power (W) required primarily depends on the CD range, the CD energy management mode and on the total vehicle weight. For instance, a PHEVx operating in CD  blended mode would require less power than the one operating in CD all-electric mode. The   peak power is generally assumed to remain constant as the AER increases [Rousseau et al., 2007].  Note also that the P/E ratio decreases with increased AER (hyperbolic behavior). This is due to the linear relationship between the available battery energy and the AER, although the  power remains nearly constant as AER increases (see e.g. [Rousseau et al., 2007]).

Lifetime, safety, costs and others •

Calendar life: it is defined as the 'ability of the battery to withstand degradation over  time' [Axsen et al., 2008]. 10-15 years is generally assumed to be a sufficient calendar  life4.

•

Cycle life. Lifetime requirements depend on the energy management mode (i.e. CD and/or CS modes) and therefore the number of micro and full discharged cycles. As HEVs operate in CS mode, they require sufficient micro-cycles which is not the case for BEVs which need sufficient full (deep) cycle life (CD mode exclusively). PHEVs   batteries must comply with both characteristics which is quite challenging. They should be able to undergo deep discharge cycles during the CD mode (probably 3-5 thousand deep discharge cycles are a reasonable target) and shallow cycles in the CS mode.

•

Safety and thermal management requirements (meet safety standards, crash worthiness, etc.).

•

Cost of the battery pack (in €/kWh and in €/kW). The battery cost increases with extending all-electric range. It remains the main barrier for the deployment of PHEVs.

•

Usable SOC window (%). The SOC window has slight impact on the fuel consumption but can significantly impact the costs. It has to be maximised while satisfying cycle and calendar life requirements [Markel and Simpson, 2006].

•

Recharge time (h). Fast recharge times are necessary for PHEVs, but this also affects the life of the battery.

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As pointed out by [Pesaran, 2007] 'currently CARB requires 10 years warranty for AT PZEV batteries but most consumers expect the  batteries to last the average life of vehicles, i.e. 15 years'.

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•

Life cycle issues (e.g. availability of lithium resource, recycling).

•

Influence of vehicle mass: the vehicle mass (through additional battery weight) slightly increases with the AER, but this effect is somewhat limited. Note that the electricity consumption (in Wh/km) increases linearly with the vehicle mass, around 6-7 Wh/km for every 100 kg in vehicle mass added [Rousseau et al., 2007].

3.4.2 State of the art and anticipated developments  Battery performances

  Nickel Metal Hydride (NiMH) batteries are the current typical batteries used by car  manufacturers in mass-produced HEVs (e.g. Toyota). However NiMH batteries are considered to have reached their maximum potential. For the future, experts do not expect significant new technical improvements and cost reductions (see e.g. [Anderman, 2008; Kalhammer et al., 2007; Kromer and Heywood, 2007]). Car makers are moving to lithium-ion5 batteries, especially because they offer energy density higher than what NiMH batteries do. They are also characterised by the absence of memory effects and low self-discharge rate. They are seen as the best option to meet the energy storage requirements not only for PHEVs, but also for BEVs and HEVs, at least in the short to medium term. Li-ion batteries offer a wide field of new developments and have not yet achieved the same maturity level as for NiMH batteries (see Figure 4). As underlined by the IEA [IEA, 2007] ''for PHEV, the key additional breakthrough appears to be lithium-ion battery technology, as the energy density has continued to improve in recent years. At the same time, the energy density of other battery technology has remained constant''. Even if R&D efforts are still needed to cope with longevity and safety problems (see e.g. [Kalhammer et al., 2007; Karden et al., 2007]) Li-ion batteries have been testing intensively worldwide and are already used on many PHEV prototypes.

Figure 4: Evolution of the energy density (Wh/litre) of Li-ion batteries, compared to NiMH and NiCD technologies Source: [IEA, 2007] (taken originally from Shinsuke Ito, EVS-22 Plug-in Hybrid Electric Vehicle Workshop) 5

Note that behind the term 'Li-ion batteries' there is a set of different technologies.

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Improvements in specific energy of Li-ion batteries are crucial for their deployment. Different goals regarding battery performances of PHEVs have been set by the U.S. Advanced Battery Consortium (USABC), the MIT and EPRI [Axsen et al., 2008]. The USABC considered two battery types: a high power/energy ratio battery providing 10 miles of AER (PHEV10) in a SUV vehicle of 1950 kg and a low-power energy ratio battery  providing 40 miles of AER (PHEV40) in a midsize sedan of 1600 kg. The MIT analyzed the goals for a midsized sedan with a 30 miles CD range in blended mode. EPRI considered a PHEV20 and PHEV60 midsized sedan. Different driven cycles were considered: USABC used the Urban Dynamometer Driving Schedule (UDDS), MIT used UDDS as well as the Highway Fuel Economy Test (HWFET) and US06 schedules (part of the Supplemental Federal Test Procedure that is characterized by   being more aggressive) and finally EPRI used a driven cycle that included the other ones (UDDS and HWFET). In all cases, the battery goals covered power, energy, life and cost goals. These goals are dependent on the assumptions made about PHEV design, drive cycle, vehicle and battery weight and recharge behaviour.

Table 1: PHEV assumptions and battery 'goals' (long-term development) Source: [Axsen et al., 2008]

 Battery costs: current trend and expectations

The cost of Li-ion batteries (i.e. at cell, module or pack level) includes material cost (e.g. anode/cathode materials), manufacturing cost and other costs (e.g. R&D, marketing, transportation). Material costs account for ~75% of the total battery pack cost while manufacturing and other costs represent around 5% and 20% respectively. For a more thorough analysis of battery-related costs, see e.g. [Anderson, 2009]. A list of current Li-ion battery costs is given in Table 2 [Petersen, 2009]. Current prices are in the range of 700-1000 $/kWh or even higher.

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Manufacturer

Chemistry

Current Price ($/kWh)

Target Price ($/kWh)

Enert1 (HEV)

Li-Polymer

660

N/A

Valence Technologies (VLNC)

Li-phosphate

1000

500

Altair Nanotechnologies (ALTI)

Li-titanate

1000

N/A

A123 Systems (power tool packs)

Li-phosphate

1228

N/A

2008 DOE SEGIS-ES Estimates (PV Solar battery packs)

Various

1333

780

2009 NEDO Survey Results (Average of Japanese Producers)

Various

2018

1000

Table 2: Current price of Li-ion batteries Source: [Petersen, 2009]

The high production volumes already achieved today suggest that Li-ion battery costs could significantly decline in the short term (see e.g. [Sanna, 2005]). It is for instance expected that Li-ion battery cost would fall as low as 395 $/kWh and 260 $/kWh for a PHEV10 and a PHEV40 respectively with 100000 units produced [Kalhammer et al., 2007]. The battery cost goal set by the USABC range from 300 $/kWh to $200/kWh for the PHEV10 and PHEV40 respectively. The MIT estimates that the commercialization of a PHEV30 requires a cost as low as 320 $/kWh. The U.S. Department of Energy' goal is 250 $/kWh by the year 2015. According to [Kammen et al., 2008], PHEVs would become cost efficient to consumers if   battery prices would decrease from 1300 $/kWh to about 500 $/kWh (so that the battery may  pay for itself). It is however not yet proven that costs will reduce in such a scale. Despite already important  production volumes, costs remained constant over last 9 years [Petersen, 2009]. It is thus not guaranteed that the above-mentioned targets will be met. Li-ion battery costs are expected to remain lower than NiMH batteries but the range of 600700 $/kWh is seen more realistic in the short to medium term (see e.g. [Anderman, 2008]). Figure 5 shows a possible (rather optimistic) evolution of Li-ion battery pack cost for PHEV40 by 2010 and 2020.

Figure 5: Battery Pack Supply Chain Cost Breakdown Source: [Anderson, 2008]

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3.4.3 Battery characteristics The following (Table 3) proposes typical ranges for the key parameters for batteries in relation with different vehicle types to be considered later when considering their energy and cost performance (section 4.4 and 5.2 respectively). HEV

BEV

PHEV

0

150-200

10-60

NiMH

Li-ion

Li-ion

Total capacity (kWh) (1)

1.3

30-60

4-30

Specific energy (Wh/kg)

46

110-160

110-160

200-350

400-600

400-600

AER (miles) Material

Energy density (Wh/l) Peak power (kW)

27-35

Specific power (W/kg)

1300 (2)

Battery pack weight (kg)

29

Calendar life (years)

10-15

Deep cycle life (number of cycles) Specific cost (€/kWh)

40-100 1500

500-1500

200-500

70-190

10-15

10-15 >2500

600

750-1500

Table 3: Typical battery performance for the near term (medium car) (1)

Obtained by multiplying the nominal capacity (in C or Ah) by the nominal voltage (V). For the Toyota Prius III, we find 6.5Ah*201.6V=1.31 kWh. (2) 28 modules weighting 1040 g each

Variation of parameters vs. AER

All other things being equal, extending the AER of PHEV (e.g. from 20 to 60 miles) will modify some parameters as follows: •

•

•

•

The peak power (W) is generally assumed to remain constant with the AER, but can vary depending whether we consider CD all-electric or blended mode. The energy capacity (kWh) varies linearly with the AER (see Figure 6), whose the slope is function of the vehicle mass (category). The battery pack weight increases with the AER, typically from 70 kg (PHEV20) to 190 kg (PHEV60). The electricity consumption (Wh/km) is assumed to increase linearly with the vehicle mass (around 6-7 Wh/km for every 100 kg added, see e.g. [Rousseau et al., 2007]) with a similar slope for each vehicle category.

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Figure 6: Usable energy battery requirements for different AER Source: [Rousseau et al., 2007]

Table 4 gives the typical capacity storage as required by different AER in the case of a midsize car. HEV

BEV

PHEV (all)

PHEV-20

PHEV-30

PHEV-40

PHEV-60

AER (miles)

0

150-200

10-60

20

30

40

60

Material

NiMH

Li-ion

Li-ion

Li-ion

Li-ion

Li-ion

Li-ion

Total capacity (kWh)

1.3

30-60

4-30

4-8

8-12

12-16

20-30

Table 4: Typical capacity storage as required by different AER (mid-size car case)

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4 Tank-to-wheel energy performance 4.1

Introduction

The comparison of the energy performance of EDVs with conventional ICE or with HEV technologies has to be made on a well-to-wheel (WTW) basis, considering the final energy required to drive the power-train (TTW), and the indirect energy consumption by the upstream energy transformation processes (WTT part). The WTT energy consumption from ICE cars accounts for all the processes from oil extraction to refinery processes. In the case of BEVs, the WTT energy use stems from the generation of the electricity used to drive the car. In the case of PHEVs, the WTT energy consumption from both fuel and electricity production has to be taken into consideration. The WTT energy use part - and resulting GHG emissions - attributed to electricity generation will depend on the power generation mix and on the time when the electricity is consumed to recharge the battery. These factors will be analysed in a subsequent assessment. Therefore, the following concentrates on the TTW aspects (or final energy consumption). As a result of its ability to drive a certain distance on CD mode, PHEVs have the potential to avoid fuel consumption. The "fuel displacement" is commonly referred to in the literature characterizing the energy performance of PHEVs6. This information is primarily relevant when energy security aspects are looked at. Fuel displacement - and, replacement with electricity consumption -, indeed means a more diversified energy supply mix. The sole indication about the fuel displacement may however be misleading as the fuel consumption avoided (compared to a reference car – be it a conventional ICE or a hybrid car) doesn't necessarily mean that the "fuel displaced" is substituted by a same amount of  electricity. A full energy performance assessment of PHEV implies to quantify both the fuel and the electricity consumptions over the considered distance driven. Compared to BEVs (that exclusively use electricity) and to HEVs (for which fuel is the sole source of energy7), the final energy consumption equation for PHEV is more complex. As illustrated in Figure 7, it will depend on the distance travelled on all-electric range, which will be influenced by both the charging pattern and the driving behaviour.

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 f  −  f PHEV  The fuel displacement rate is defined as: FD =  REF  where  f  REF  and  f PHEV  denote the fuel consumption of the reference  f  REF 

vehicle and of the PHEV respectively. 7 For HEVs, an amount of fossil fuels is 'indirectly' displaced through on-board production of electricity (e.g. regenerative braking).

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HEV

PHEV

BEV

100% CS

xCD+(1-x)CS

100% CD

Charging pattern

Driving pattern

Annual distance performed on electricity = f (annual vehicle-km, AER capability etc.)

Driving cycles

l/km

 Δl/km of fuel ‘converted’ in kWh/km

Driving cycles

kWh/km Tyres, body shape Weight Power train Electric motor Etc.

Tyres, body shape Weight Power train ICE efficiency Etc.

Figure 7: Level of complexity to consider when assessing the energy performance of PHEVs

Assessing the final energy consumption of PHEVs implies to take into account the following factors: Driving cycle (urban, highways, combined) • The CD mode energy management (CD 'blended' or CD 'all-electric'). This is linked to • the power train configuration (series, parallel, split). The daily distance travelled on CD mode which depends on charging (location, time • of the day, frequency) and driving patterns (e.g. average daily distance travelled). Also, the fuel displacement rate with PHEVs (i.e. based on the annual AER) will increase when the energy storage capacity is extended (PHEV60 offers more potential than PHEV20).

4.2 

Literature review

Most of the research studies assessing the energy performance of PHEVs have been undertaken by American research bodies, notably by the Massachusetts Institute of  Technology (MIT), the Electric Power Research Institute (EPRI), the National Renewable Energy Laboratory (NREL) of the U.S. DoE, the Argonne National Laboratory (ANL) but also by the International Energy Agency (IEA). Several studies (see Table 5) analysed the quantity of fuel displaced for different PHEV configurations, under different assumptions (e.g. charging time, driving models, market   penetration rates, etc.). Different approaches are used, including tests and modelling (e.g. ADVISOR, PAMVEC models). All of them concluded that the use of PHEV would displace a large quantity of fuels.

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Reference [Parks et al., 2007]

Methodology / comments ADVISOR model Colorado case study Data from HEVs converted in PHEVs

[Karner and Francfort, 2007] [Stephan and Sullivan, Based on Toyota RAV4 2008] [Kliesch and Langer, Based on converted Toyota Prius (CO2 and air emissions) 2006] PHEV10-60 fuel reduction under average driving conditions (US) [Samaras and  No quantification of fuel displacement Meisterling, 2008] Life cycle Assessment of GHG emissions [EPRI/NRDC, 2007] Potential long-term GHG emissions impacts of PHEVs in the U.S. (annual consumption, years 2010 and 2050). 9 scenarios (3 emissions intensity for the electric sector and 3 scenarios for PHEVs market penetration) [Shiau et al., 2009] Economic and environmental related impacts of battery weight and charging patterns of PHEVs [Bradley and Franck, Literature review on fuel consumption from PHEVs 2009] [Silva et al., 2009] 2 PHEVs, 2 configurations (series and parallel), 4 driving cycles (CAFE, FTP75, NEDC, JC08). Alternative approach to the SAE J1711 recommended practice The ADVISOR software is used. Influence of driving and charging patterns on FC and air   pollutants (U.S., EU and Japan) Fuel consumption, CO2 emissions, impact on electricity grid, costs. [Simpson, 2006] PAMVEC model Cost-benefit analysis FC (l/100km) and electricity consumption (Wh/km) for  PHEV2,5,10,20,30,40,50,60 under two scenarios [MIT, 2008] Deep analysis, US context UF is around 50% for a PHEV30 (for the US) Simulation results for time horizon 2035 WTW emissions and market penetration of PHEVs are analysed under different scenarios. [Kammen et al., 2008] Compared CV, HEV and 2 PHEVs (compact car and full-size SUV) GHG avoided estimated from the GREET model Cost-effectiveness analysis of PHEVs [Elgomainy et al., WTW energy used and GHG emissions from PHEVs 2009] GREET model and PSAT simulation [Dowds et al., 2009] Review on PHEVs fuel displaced, GHG emissions and their  interaction with the infrastructure. [Clement-Nyns et al., Based on TREMOVE model 2007] Consumption of electrical energy (for Belgium). [IEA, 2007] Deep analysis, using GREET model and PSAT simulations. [Gonder and Simpson, Measurement of the fuel consumption of PHEVs. 2007] Discuss the SAE J1711 recommended practice. [Gonder et al., 2007] [Kromer and Heywood, 2007]

Institute   National Renewable Energy Laboratory (NREL) Idaho National Laboratory (US DOE) Ford Motor Company American Council for an Energy-Efficient Economy Carnegie Mellon University (PA) EPRI, NRDC

Carnegie Mellon University (PA) Georgia Institute of  Technology, UC Davis IDMEC (Lisbon) University of Michigan (MI)

  National Renewable Energy Laboratory (NREL)

MIT

University Berkeley

Argonne Laboratory IEEE

of

California,

National

Universite Catholique de Louvain IEA (Annex 7) Tesla Motors Inc.,   National Renewable Energy Laboratory (NREL) Influence of driving patterns on fuel displacement rate. Based on   National Renewable Energy GPS real-world measurements. Laboratory (NREL) WTW energy use for PHEV30 TIAX and MIT Market penetration assumptions

Table 5: (Non-exhaustive) list of key references dealing with petroleum displacement of PHEVs

17

The fuel displacement potentials reported in the literature were reviewed by [Dowds et al., 2009] and are shown in Figure 8. The fuel displacement rates are associated with PHEV10, PHEV20 and PHEV40 and were found to range from 42% to 78% relative to ICEs and from 12% to 66% relative to HEVs [Dowds et al., 2009]. Such ranges are also confirmed by other  research works. It is worth mentioning that the different estimates obtained in a same study (see e.g. [EPRI/NRDC, 2007]) illustrate the large influence of the assumptions made.

Figure 8: Fuel displacement from PHEVs with varying all-electric ranges. Source: [Dowds et al., 2009] [7] = [EPRI/NRDC, 2007]; [11] = [Gonder et al., 2007]; [15] = [Kliesch and Langer, 2006]; [9] = [Letendre et al., 2008]; [12] = [Parks et al., 2007] [12](A) assumed that the PHEV charged once per day. [12] (B) assumed a PHEV charged whenever it was not in use. In scenario [12] (B), the PHEV is charged more frequently and a higher proportion of VMT is based on electricity, increasing the relative gasoline displacement.

Medium and long-term energy performances of PHEVs (2030-2050) have been analysed and compared with a reference vehicle. [MIT, 2008] estimated that in 2035, a PHEV50 would consume around 1.5 l/100km (TTW gasoline consumption only, electricity usage not included) which is roughly four times lower than a gasoline ICE at the same year and five times lower than a current gasoline ICE. The results of the EPRI study [EPRI/NRDC, 2007] are summarized in Table 6. Energy consumption 2010 Gasoline (l) Electricity (kWh) 2050 Gasoline (l) Electricity (kWh)

CV 1847

HEV 1198

1514

981

PHEV10 1049 467 859 382

PHEV20 609 1840 498 1504

PHEV40 406 2477 332 2024

Table 6: Energy consumption of different EDVs in 2010 and 2050 Source: adapted from [EPRI/NRDC, 2007]  Annual mileage: 12000 miles (19312 km); converted into litres (1 gal = 3.78 l)

18

4.3

How to measure the final energy consumption of PHEVs? 

The ability of PHEVs to drive independently (or not) from electrical and/or chemical energy make their fuel efficiency assessment a complex task. As underlined by [Silva et al., 2009], there is no worldwide consensus on how to fairly calculate them. The SAEJ1711 recommended practice8 proposes a methodology for measuring the fuel consumption and standard emissions of PHEVs for different driving cycles. New improvements have been subsequently proposed by several research works [Silva et al., 2009; Gonder and Simpson, 2007]. In the following, the emphasis is put on key aspects for evaluating the energy efficiency of PHEVs.  Influence of the CD mode energy strategy control •

CD all-electric

The CD all-electric mode means that no fuel is burnt over the first x kilometres driven on CD mode while it starts steadily increasing when the engine is turn on so as to achieve the energy   performance of a HEV (CS mode). This results in an asymptotic behaviour, as shown in Figure 9. This is for instance the case of PHEV series (e.g. GM Chevrolet Volt).

Figure 9: Fuel consumption as a function of distance driven bet ween two full charging events Source: [Shiau et al., 2009] •

CD blended

The Argonne National Laboratory analysed the energy use of PHEVs [Elgowainy et al., 2009]   based on different simulations9. They calculated the average fuel consumption of the engine in CD (blended) and CS modes based on weighting factors of 55% and 45% for the fuel consumption over an urban driving cycle (UDDS) and a highway driving cycle (HWFET) 8

SAE J1711-MAR1999., Recommended practice for measuring the exhaust emissions and fuel economy of hybrid electric vehicles, March 1999. 9 From the Powertrain System Analysis Toolkit (PSAT)

19

respectively. The results are presented in Table 7 and compared with the corresponding ICE and HEV as reference vehicles. AER 10

ICE refernce

7.26

HEV reference

5.13

AER 20

CD mode

CD mode

CS mode

AER 30

CS mode

CD mode

AER 40

CS mode

CD mode

CS mode

Motor

Engine

Engine

Moto r

En gine

En gine

Motor

Engine

Engine

Motor

Engin e

E ngine

0.99

2.17

4.96

1.07

1.93

4.98

1.28

1.39

5.02

1.28

1.43

5.07

Table 7: Fuel consumption (l/km) of PHEVs over the CD (blended) and CS modes Source: [Elgowainy et al., 2009]

The average fuel consumption (in l/100km) can be derived for each PHEV configuration, from these figures. The resulting profiles are similar to those from Figure 9, at the exception that the CD mode is assumed here to operate in blended mode (i.e. not 100% electric, gasoline is also used to power the vehicle during the CD range). 8

7

6   m    k    0    0 5    1   r   e   p   s 4   e   r    t    i    L

PHEV10 PHEV20 PHEV30

3

PHEV40 ICE

2

HEV

1 2

40

80

120

160

200

240

280

320

360

400

440

480

520

560

600

Distance (km)

Figure 10: Average fuel consumption (electricity excluded) as a function of distance (own calculations based on [Elgowainy et al., 2007])

 Average daily distance travelled: Utility Factor 

The above estimations provide the fuel consumption as a function of the distance travelled. Realistic estimates of the average daily (or annual) fuel and electricity consumption by a PHEV will depend on the average daily distance travelled and on the likely distances driven in CD mode and CS mode respectively. For instance, [Silva et al., 2009] report the following average commuting distances: 30 km for  the U.S., 5-30 km for Europe and 20 km for Japan. In their analysis, a 20 km average distance was assumed. Considering that around half the passenger cars in the U.S. drives less than 25 miles (40 km) a day and 80% less than 50 km (see e.g. [Sanna, 2005]), this distance could be easily covered by PHEVs running on the sole electric power (considering an AER of typically 30-100 km). They conclude that if the vehicle is daily recharged, large amount of fuel could  be displaced annually. 20

Given a distribution of driven distances in a region considered, the share of kilometres travelled on all-electric over the year has to be determined to estimate the fuel displacement. The estimates made at national level in the literature introduce the Utility Factor (UF) which is defined as the ratio of the vehicle-km driven on all-electric over the total annual vehiclekm. UF  =

VKT  ELEC  VKT  ELEC  + VKT FUEL

VKT  ELEC  is the annual vehicle-km driven on electrical energy VKT FUEL is the annual vehicle-km driven on chemical energy

The total fuel consumed (fuel equivalent) per year is then given by: F TOT 

=

F CD * UF  + F CS * (1 − UF )

where F CD and F CS are the fuel consumed during CD and CS operation modes respectively. Typically, the shortest the daily trips, the higher the utility factor will be since most of the distance will be driven on electric mode (depending of course on the AER capability of the PHEV). The typical utility factor in U.S. is estimated to be around 50% for a PHEV with a 50 km AER (see e.g. [MIT, 2008]). [EPRI/NRDC, 2007] assumes the utility factors to be 12%, 49% and 66% respectively for PHEV10, PHEV20 and PHEV40 (in miles). An example of UF curve is given in Figure 11 for the U.S. [Elgowainy et al., 2009]. These indicative UF could be used as a first estimate for Europe but EU specific estimations should be made later. A first indication to this end relates to the shares of the different road modes in the annual distance driven. The assumptions in TREMOVE for the year 2005 are as follows: 19%, 58% and 23% of vkm are driven on respectively urban motorways, non urban roads and urban roads. If urban and non urban roads are assumed to be linked to short distance trip, it can be concluded that ~80% of the total distance driven consist in short distance trips.

Figure 11: Typical Utility Factor curve used for the U.S. [Elgowainy et al., 2009]

21

 Influence of charging patterns

As seen before, the charging pattern of PHEV users is of high importance. Questions are how often, where and at what time of the day would the battery be recharged? These factors introduce a non-negligible level of complexity for assessing the energy performance of  PHEVs. Many studies assume that the vehicle will be recharged at home every day, mainly overnight. But such an assumption could significantly distort the results, and, possibly overestimate the  benefits of PHEVs.

4.4

Energy performance of EDVs: first estimations

A simplified model has been elaborated in order to derive first estimates of the total energy consumption (electric and chemical energy) of different vehicles, and to provide a comparison with the current new conventional cars purchased in Europe. The following describes first, the reference cars considered, and then, the assumptions made to calculate the energy consumption of the corresponding PHEVs. Three AER values are considered, respectively 20, 40, and 60 miles. The estimates correspond to "type-approval values". In the following, the focus is on the medium-size car segment, which in terms of typical conventional car engine size is in the range 1400-2000 cc. However some background information about other vehicle size segments is also referred to (reference cars). This leaves the possibility to later extend the estimates for the other relevant segments. This should cover  the upper segment (>2000 cc). On the other hand, one could wonder whether if PHEV will significantly penetrate the market in the lower segment (<1400 cc). Given the additional cost, the new technology would indeed  be proportionally excessive for a significant market penetration. Also, it could be considered that where small cars are predominantly driven in urban areas, BEVs could be the most logical step made by the consumer. It has to be stressed that the approach followed here could subsequently be refined (in the light of better and more complete data and of better understanding of the technology aspects). Refinements could consist in better modelling to reflect effects such as driving cycles (urban versus non-urban, etc.), real-world driving patterns (effects of speed, acceleration), driving charging pattern (charging frequency). One option for that could be to use existing data to  better model the CS mode, in the light of existing measurements of existing HEV car models.

4.4.1 Reference cars energy performance and cost The reference cars are defined in terms of their fuel consumption on the basis of the data about CO2 emissions given by the European monitoring database. The latest data available, at the disaggregated level (vehicle size segmentation) is for the year 2006 and is used in TREMOVE. Correction factors are used in TREMOVE to adjust these emissions for the following years.

22

Table 8 gives the corresponding fuel consumption (MJ/km) for conventional cars and for  HEVs in the medium-class segment. The figure corresponding to the medium gasoline car  was derived from the type-approval emission value for the second generation Toyota Prius (104 g/km). The values for the other car segments are first indicative estimates of what the hybrid power train technology would result, in relative terms, in a fuel efficiency improvement similar to what is expected for the medium-gasoline car. Conventional car (MJ/km)

HEV (MJ/km)

car <1.4l - petrol

1.97

1.16

car 1.4-2.0l - petrol

2.46

1.45

car >2.0l - petrol

3.15

1.85

car <1.4l - diesel

1.61

0.95

car 1.4-2.0l - diesel

2.00

1.18

car >2.0l - diesel

2.73

1.61

Vehicle category

Table 8: Average fuel consumption for new conventional and HEV in 2005

4.4.2 Battery specifications The battery characteristics considered are based on the ranges given in section 3.4.3.

4.4.3 Energy efficiency •

CD mode energy strategy

The definition of Charge Depleting mode (CD) refers to a CD all-electric mode, meaning that the vehicle will drive the first x kilometres on the battery energy and turns on the engine when the battery has reached its minimum SOC level (CS mode). This implicitly assumes that the  batteries are charged every day. Such energy management strategy is mainly the one used by PHEV series (e.g. GM Chevrolet Volt) for which the vehicle is basically an electric vehicle equipped with a backup source of energy (petroleum-based or even biomass-based fuels). Several assumptions are needed to estimate the electricity consumed over the CD range (kWh/km). For BEVs, the electricity efficiency is derived from [Perujo and Ciuffo, 2009] while for PHEVs, it is (first assumption) fixed at 123 Wh/km [Silva et al., 2009]. BEV 100 154 194

Small Medium Big

Table 9: Electricity consumption for BEVs (Wh/km) Source: [Perujo and Ciuffo, 2009]

•

 Energy efficiency over the CS mode

Once the CD mode is over, the engine is turned on and the vehicle is assumed to behave as a conventional hybrid (Charge Sustaining) mode. Therefore fuel consumption in CS mode is assumed to be provided by Table 8.

23

 Remark: The effect of battery mass increment as a result of increased AER was not taken into account in the calculation.

Figure 12 shows the calculated energy consumption over a 50 km distance for different vehicles in the case of the medium-size car. Over the distance considered, due to the larger  AER, PHEV40 and PHEV 60 (but also the BEV) have much lower final energy consumptions compared with the PHEV20.    l    l   u    f    2 80   n   e   e 70   w    t   e   s 60    b   t   n   n   e 50   o   v    i    t   e   )   p   g   J 40   m   n   M    (   u   i   s   g   r 30   n   a   o   h   c   c 20   y   g   r 10   e   n    l 0   a   n    i    F

HEV

BEV

PHEV20

Fuel consumption

PHEV40

PHEV60

Electricity consumption

Total distance (km):

50 

Figure 12: Energy performance of different electric vehicles (medium gasoline car) PHEVx with x in miles

Similar calculations made for a large range of distances result in different energy consumption. This is depicted in Figure 13, giving the total petrol equivalent (in l/100km) as a function of the distance.

4.5

4

3.5

  m 3    k    0    0    1    /  . 2.5   q   e    l   o   r 2    t   e   p   e   r    t    i    L 1.5

HEV PHEV20

1

PHEV40 PHEV60

0.5

0 10

20

30

40

50

60

70

80

90

100 110 120 130 140 150 160 170 180 190 200

Distance (km)

Figure 13: Gasoline equivalent consumption vs. total driving distance

Given the fact that, on the average, 80% of the EU passenger car traffic takes place on urban and non urban roads (the rest is in motorways), it can be considered, as a first approximation, that this urban traffic represents 20-50 km average daily distance trips. Highway traffic typical trip distance would be of the order of magnitude of 100 km. 24

The average fuel consumption (MJ/km) derived from the above approach for those two typical trip distances are given in Table 10 below. These values would represent a first input in view of the modelling work with TREMOVE and TIMES. km

Coventional

HEV

fuel consumption

MJ

98

58

0

11

0

0

electricity consumption

MJ

0

0

22

14

18

18

Total

MJ

98

58

22

26

18

18

fuel consumption

MJ/km

2.5

1.4

0.0

0.3

0.0

0.0

electricity consumption

MJ/km

0.0

0.0

0.6

0.4

0.4

0.4

Total

MJ/km

2.5

1.4

0.6

0.6

0.4

0.4

40

BEV

PHEV20

PHEV40

PHEV60

km

Coventional

HEV

BEV

PHEV20

PHEV40

PHEV60

fuel consumption

MJ

246

144

0

98

51

5

electricity consumption

MJ

0

0

55

14

28

43

Total

MJ

246

144

55

112

80

48

fuel consumption

MJ/km

2.5

1.4

0.0

1.0

0.5

0.0

electricity consumption

MJ/km

0.0

0.0

0.6

0.1

0.3

0.4

Total

MJ/km

2.5

1.4

0.6

1.1

0.8

0.5

100

Table 10: Input parameters for energy performance 2.5

2.0

fuel consumption

electricity consumption

1.5   m    k    /    J    M 1.0

0.5

0.0 Coventional

HEV

BEV

PHEV20

PHEV40

short distance

PHEV60

PHEV20

PHEV40

PHEV60

long distance

Figure 14: Comparison of average fuel/electricity consumption of different EDVs

4.5 • • • • • •

Need for further work  Refine where possible the method Driving cycles (urban versus non urban) Driving patterns (effects of speed, acceleration), real-life versus certification values Driving charging pattern (charging frequency) Define utility factor for Europe? Characteristics of BEVs and energy performance to be reviewed 25

5 Vehicle costs 5.1

Literature review 

Compared to ICE cars, PHEVs cars entail additional manufacturing and maintenance costs: •

Manufacturer costs result from engine and transmission, motor/inverter, controller,   battery and charger as well as certain vehicle upgrades. In total, the additional manufacturer costs are reported in a range $4000-10000 compared to conventional gasoline vehicles, and roughly 10-30% higher than for conventional HEVs ($20004000 for a sedan; greater than $5000 for a SUV). Cost of batteries accounts for the higher contribution (~50%) and obviously increases with the battery storage capacity as determined by the AER (see e.g. [Pesaran and Markel, 2007]).

•

Maintenance costs mainly depend on the battery replacement frequency: around 80000 km for lead acid batteries and around 240000 km (150000 miles) for Ni-MH and Liion batteries.

Costs comparisons are found in the literature for near-term and long-term horizons (see Table 11). This shows a wide range of additional cost estimations when compared with the corresponding conventional ICE car, but overall, the expected extra costs are important for all 3 time horizons. Costs are expected to decline over time and the expected decline seems to be the biggest over the mid-term. One needs however to ensure that the different sources have comparable assumptions behind the different figures.

26

ICE

HEV

PHEV10

PHEV20

PHEV30

PHEV40

PHEV50

PHEV60

Near term total cost

$

additional  cost 

$

total cost [Kromer and Heywood, additional  2008] cost 

$

[Simpson, 2006]

[Lipman and total cost Delucchi, 2006] from additional  cost  ANL total cost EPRI, based on [Graham, additional  2001] cost 

23 392

% ICE

$ 

28 773

34 180

38 935

42 618

45 655

5 381

10 788

15 543

19 226

22 263

24 770

26 792

23%

46%

66%

82%

95%

106%

115%

1 900

3 000

4 300

48 162

50 184    

6 100

% ICE 

$

22 500

$ % ICE

$

18 984

$ % ICE

26 520

29 740

4 020

7 240

18%

32%

0%

23 042

24 966

29 523

4 058

5 982

10 539

21%

32%

56%

1500-4000

4000-6000

7400-10000

 

8% - 22%

22% - 33%

41% - 55%

 

3 266

8 436

13 289

14%

36%

57%

   

   

Mid-term

[Graham, 2001]

total cost

$

additional  cost 

$

18 000

% ICE

Long term [Simpson, 2006]

total cost

$

additional  cost 

$

23 392

% ICE

Table 11: Different cost estimations found in the literature

Those important extra manufacturing costs will obviously largely determine the future commercialization of PHEVs. It has to be noted that the above figures assume that costs of conventional cars will not change over time although one could assume that those cars are likely to be fitted with new abatement technologies (e.g. extra downsizing) which could entail manufacturing cost changes. The overall picture needs also to be looked at, considering all costs components, including maintenance and fuel costs. Such a comparison was made by [Karplus et al., 2009], considering a PHEV30, and using the long-term cost estimates and energy performance from [Simpson, 2006]. He derived a 8 year   payback period.

5.2

Vehicle cost comparison for the EU 

The above discussed cost figures provided a first overview of the costs compared to a corresponding ICE car for which characteristics are representative of the US market. Using those values as such for Europe could give a wrong picture and it is thus necessary to use the available information the appropriate context.

27

   

Similar to what was done for the energy consumption in section 4.4, the following elaborates a simple approach to derive vehicle cost estimations for BEVs and PHEVs for typical car  models purchased in Europe. This is illustrated with the medium-gasoline car model. As a first step, the EU27 sales-weighted average manufacturing cost for the ICE petrol new car purchased in 2006 is derived from the TREMOVE model (€11706). Costs for the corresponding hybrid car are then derived from the recent report by the AEA [AEA, 2009]. This report has reviewed the potential and costs to reduce emissions from cars, considering conventional ICE abatement technologies and hybrid power train. Cost curves are given, giving the abatement cost as a function of the CO2 emission reductions from the current new conventional car (year 2006). The emission reduction level assumed for the medium car is derived from the second generation Toyota Prius (type approval emissions: 104 g CO2/km). The corresponding extra manufacturing cost is €2800. Based on assumed battery costs (see section 3.4) and assumed battery power, the extra costs for PHEVs are derived (see Table 12). Conventional car

Battery cost

€

total manufacturing cost

€

11 706

HEV

BEV

PHEV20

PHEV40

PHEV60

1 125

9 525

15 600

19 800

14 502

20 106

26 181

30 381

Table 12: Battery cost and manufacturing costs for the near term in Europe

5.3 • • •

Need for further work  Costs for BEVs. Maintenance costs to be determined according to the assumed battery durability. Learning effects and costs for the longer term.

28

6 Battery charging options and infrastructures 6.1

Introduction

The incremental vehicle costs together with the availability and incurred costs from possible   battery charging parameters will largely determine the large scale deployment of BEVs and PHEVs and, also, its effects on e.g. the electricity grid and sector. This will also determine the real environmental benefit stemming from the fuel displacement to electricity. Infrastructure geographical availability can for instance influence the required on-board energy storage energy capacity and vehicle performances. Battery charging aspects include various interlinked issues, which are discussed in the following sections: 1. Which technical solutions and infrastructures will be available and will be implemented and, at what costs? 2. How and when the car owner will most likely charge the empty batteries? 3. Which options can be realistically used by electric utilities to remotely control the aggregated charging curve to best match with the electricity production mix?

6.2

Battery charging options

Battery recharging requires different equipments: the physical recharging interface (the 'plug' or inductive\conductive plate) and recharging protocols (the conversation between the vehicle and a fast charger) and also, in case of plug-in, a suitable connection to the electric grid must   be provided. The design of the charger and the charging infrastructure are different in each country according to the electric infrastructure. PHEVs have been designed using conductive or inductive chargers. While inductive chargers have the advantage of intrinsic safety and pre-existing infrastructure, the conductive ones have efficiency advantages (87% charger efficiency [Pratt, 2007]), are generally lighter  weight and more compact and can allow for bidirectional power flow [Bradley and Frank, 2009]. In Europe a direct conductive connection is preferred to the inductive connection which is often used in USA and Japan. The power demand on the grid by a PHEV will be a function of the voltage and amperage of  the connection to the grid. Three possible methods can be implemented to recharge the battery. In a charge infrastructure review, [Morrow et al., 2008] describes three charge "levels" defined by the US Electric Power Research Institute (EPRI): •

The level 1 method uses the US standard 120 VAC, 15A or 20A branch circuit, used in the residential and commercial buildings. This delivers a 1.44 kW maximum power. This method would for the user, to install a new dedicated circuit to avoid overload. This is the most immediate solution.

29

•

The level 2 method is based on a 240VAC, single phase, branch circuit with up to 40A, requiring a dedicated circuit. Under 15A, the maximum charge power would be 3.3 kW. This method could be implemented for both residential and public charging.

•

The level 3 is the method suitable for fast charging through public facilities, based on 480 VAC, three-phase circuit, and enabling 60-150 kW charging power. This option implies a number of specific safety precautions.

Level 2 method would be enough to ensure a "rich" charging infrastructure. In addition to these charging facilities, options are also currently envisaged to make the charging even faster and, also save the driver to charge the battery himself. Such option consists in changing the discharged battery packs by charged battery packs. However, this case requires an important infrastructure to store, monitor, recharge…etc, batteries. Table 13 summarises the technical features, infrastructure requirement and costs implied by the different charging methods. The costs include labour, material and permit costs.

Level1

Level2

Level3

Voltage/Amperage

US: 120 VAC/15A; EU: 220 VAC

US: 240 VAC/40A; EU:240 VAC

480 VAC

Charging power

1.44 kW in US, higher value in EU

3.3 kW (15A)

60-150 kW

Charging speed for a 10 kWh battery

~5-8 hours, even faster in EU

~1-2 hours

<10 minutes

Compatible facility

Private charging facility

Private and collective charging facilities

Collective charging facilities

Higher battery capacity required On-board charger

Higher battery capacity required On-board charger

Low battery capacity required

charging

Vehicle equipment requirement

Cable from electricity outlet to the vehicle

Infrastructure requirement

Typical number chargers

Total installation charger

New dedicated circuit of

implied cost per

Stationary charger Cable from electricity outlet to the vehicle

Stationary charger Three phase

New dedicated circuit

1 single house, 5 if complex of apartments 2146 USD for single house, 1520 for apartment complex, 1852 USD for commercial buildings

878 USD

ND

Table 13: Methods for recharging Source: [Morrow et al., 2008]

It has to be noted that charging implies transmission and distribution loss (around 8%, see e.g. [Pratt, 2007]).

30

6.3

Expected recharging time and implied charging infrastructure

The expected recharging time, together with the car use pattern itself should ideally be assessed in the light of known car trip and built infrastructure settlement. The immediate expectation is that PHEVs would be charged overnight on a standard 220V outlet, in garages for instance10. This would, in most cases, result in the optimal aggregated  battery charging profile as it would be associated with low demand (off peak period). This assumption could however be too simplistic for different reasons. On the one hand, owners of houses with garage are more likely to live away from urban zones where BEV/PHEV cars are the most likely driven. On the other hand, if this represents the sole charging option, this could represent a limitation to the large scale penetration of those new cars. The assumptions that recharging would occur after each trip and overnight are contradicted by surveys made on a (limited11) sample of early PHEV in the U.S. (see e.g. [Morrow et al, 2008]) which instead suggested that only 19% resulted in a charge event and the vehicles were predominantly charged during daytimes hours. In general, it is suggested that the  preferred time for charging (in the absence of any incentives) is likely to be as soon as they are within easy access to a plug. Incentives to modify customer choices include electricity  pricing schemes favouring nighttimes. [Morrow et al., 2008] also used the US National Household Travel Survey12 to assess possible scenarios about battery infrastructures, suggesting that: •

~65 km of charge-depleting range is necessary on an average PHEV if no infrastructure is available outside of the owner's primary residence.

•

The range could be lowered to ~20 km if public charging infrastructure is available.

The availability of public charging would thus make PHEV driving more flexible but would also result in a reduced required onboard energy storage capacity, with also consequences on the energy performance and costs of the vehicle. The deployment of such infrastructures is actually already planned or initiated in various countries. The costs of the public infrastructure of course need to be considered to conclude on the net cost efficiency of that option. [Morrow et al., 2008] also conclude that "the overall transportation system cost can be reduced by providing rich charging infrastructure rather  than compensating for lean infrastructure with additional battery size and range. Beyond the initial cost savings, the far shorter life of a battery versus charging infrastructure ensures that  infrastructure will continue to accrue savings over its operating life." The questions to be addressed are then which is the station density needed (for a given market   penetration) and who should bear the costs of the infrastructures, especially in case Government decide on its deployment. 10

In the US, more than 30% of households park their vehicles in a garage or carport [Santini, 2006]. 9 vehicles only 12 Bureau of Transportation statistics: http://www.bts.gov/help/national_household_travel_survey.html (last data for 2001-2002). 11

31

When evaluating charging options in EU, infrastructure scenarios would include: Residential garage charging • Apartment complex charging • • Public facility charging, including e.g. workplaces, public parking, dedicated recharging stations

6.4 • • • •

•

Need for further work  Use EU or MS related surveys to conform above assumptions Check EU terminology if any to characterize the different charging methods Station network density needed (for a given market penetration) Who would bear the costs of the infrastructures, especially in case Government decides on its deployment? Document the different national plans

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7 Impacts on, and role of electricity grid operators 7.1

Introduction

Different aspects of the electricity grid and power generation could be impacted by a large scale penetration of EDVs. For instance, if batteries from a growing electric-drive vehicle fleet are not predominantly charged overnight, this could result in an inefficient marginal electricity generation. •

[Dowds et al., 2009] discusses some possible physical impacts on the transmission and distribution system impacts. Transformers for instance could be subject to increased average operating temperatures under an additional load such that required  by EDVs. This could shorten their life, thus adding costs to the electricity grid.

•

If the aggregated battery charging profile includes a significant coverage of the onpeak period, this would of course result in potential power supply shortage and, in any case to the generation of the least efficient electricity units.

•

The main environmental arguments about EDV come from the idea that their batteries should be storing electricity from the lowest carbon emitting sources, namely nuclear  energy and renewable energy. Regarding the last source, the challenge is then to make the two demand and supply load curves coincide.

Depending on both the battery load curve - which depends on the time for recharging and charging power - and how far and innovative management methods are exploited by the electricity grid operators, the electricity transport and generation capacity will be impacted by the new vehicle fleet. In the absence of such management method, and without upgraded generation capacity, according to the study made by [Hardley, 2006] for the region covering South Carolina, North Carolina and one part of Virgina, the likelihood that generation amounts will not be sufficient to meet demand could be slightly increased with the introduction of EDV up to 7.9 days in 10 years (6.1 days in 10 years without EDV  penetration). Those concerns make that the operators of the electricity grid have to deploy new techniques to monitor, and remotely control the electricity demand. This is actually already one of the elements of the role of electricity grid operators in demand side energy management. Beyond such a mono-directional power flow management (power flow from the electricity grid to the vehicle battery), more integration methods are explored and envisioned to make this in the two directions (electricity grid to vehicle and vice versa). These innovations are also to be considered in the framework of the research and development efforts towards a smart and reliable grid, as needed by the growing role of  distributed energy resources (DES), including intermittent renewable energy resources.

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7.2

From mono-directional management 

to

bi-directional

power

flow 

In the first case, smart meters would track electricity use in real time. Thus, coupled with such a system, smart chargers, which would include a charger that runs on a timer, could ensure that the plug-in batteries are charged only when the electricity is at its cheapest, saving consumers money. Moreover, utilities could temporarily turn off chargers in thousands of  homes or business to keep the grid form crashing after a spike in demand. In the more integrated system, the "Vehicle to grid" – V2G, the electric drive vehicle (EDV) is capable to send power to the electric grid generally when it is parked. V2G concept was   proposed by Amori Lovins in 1995 and afterwards several developments have been done especially by Willet Kempton. At present, an automobile capable of vehicle to grid (V2G) interaction is sometimes referred as 'mobile energy' or 'smart charging' [Williams and Kurani, 2006, 2007]. With the V2G technology, the unused electric car could supply electricity to the grid when required. It makes sense if most vehicles would remain parked at any point of time. The main  benefits are: •

Profitable grid management, especially for ancillary services (A/S). A/S support the stable operation of the electric system, and consist in on-line generators synchronized to the grid to keep frequency and voltage steady, ready to be increased/decreased instantly (2-3 min) via automatic generation control (AGC) and spinning reserves [Turton and Moura, 2008]. It has to be guaranteed 24 hours/day 7 days/week, and account for 5-10% of electricity cost. V2G could help attenuating those costs (see e.g. [Tomic and Kempton, 2007]).

•

Emergency power supply provided by the V2G very fast response and clean power  source that can replace diesel generators.

•

V2G technology is also envisioned as a solution to the intermittency of renewable energy sources of which role is expected to grow in the future. V2G would indeed  provide both backup and storage that are the typical ways to cope with intermittency. It is suggested that the V2G technology could simultaneously accelerate the   penetration of EDV and allow a reliable high penetration of renewable electricity [Kempton and Tomic, 2005].

•

Electric power support – V2G could power traction spikes for local rail, and use a variety of billing/charging schemes to encourage customers' participation.

Existing analyses show that V2G opportunities and their financial value vary with the type of  vehicle and the power market [Kempton and Letendre, 1997; Kempton and Letendre, 1999; Kempton and Kubo, 2000; Hawkins, 2001; Tomic and Kempton, 2003]. As reported by [Tomic and Kempton, 2005], V2G is limited by: •

the current-carrying capacity of the wires and other circuitry connecting the vehicle through the building to the grid;

•

the stored energy in the vehicle divided by the time it is used. 34

At vehicle level, the vehicle’s power electronics needs top be sufficient. This doesn't represent a strong constraint because all electric-drive vehicles are equipped with power electronics which generate clean, 60 Hz AC power, at power levels from 10kW (for the Honda Insight) to 100kW (for GM’s EV1) [Letendre and Kempton, 2007]. Most of the required power is already built-in and paid for as part of the transportation function. However, three elements are required for V2G [Tomic and Kempton, 2007]: •  power connection for electrical energy flow from vehicle to grid. • control or communication device to enable the grid operator determining available capacity, requested power from the vehicle, and meter the result. •   precision certified metering on board the vehicle to track energy flows to measure exactly how much power a vehicle provided and at which times. Also, potential challenges, relating to standards need to be resolved [smartgridnews, 2008]: Communications standards and networks • Connection standards (Where does the intelligence reside: in the vehicle, at the utility, • or at a third-party aggregator and how do they talk to each other?) Integration of control methods • Then pricing and cost sharing issues have to be addressed: Appropriate payment and subsidy schemes (How are customers rewarded or  • compensated for the use of their batteries?)  Necessary infrastructure investments and cost sharing schemes (Who puts in the new • two-way, smart metered plugs for all the homes, the apartment buildings, and the  parking garages?)

Acceptance of these technologies as a new grid resource will require rethinking many of our  current assumptions about what is a load and what is a generator, and the proper  implementation of pricing strategies within the grid. Finally, extra vehicle costs could be significant. According to [Wellinghoff and Kempton, 2007] the cost of a vehicle with V2G at 20 kW would be around $65000 (€46952) (considering a demonstration project of 300-400 V2G vehicles). Recently, the Michigan Public Service Commission [MPSC, 2008] established that the higher  PHEV penetration depends on smart grid infrastructure research and developments. Thus, the US Department of Energy’s (DOE) Office of Electricity Delivery and Energy Reliability has identified seven principal characteristics of a smart electric grid to allow PHEV penetration: •

•

•

•

Self-Healing - a grid able to rapidly detect, analyze, respond, and restore from  perturbations. Empower and Incorporate the Consumer - a grid able to incorporate consumer  equipment and behaviour. Tolerant of a Security Attack - a grid that mitigates and stands resilient to physical and cyber security attack. Provides Power Quality Needed by 21st Century Users - a grid that provides a quality of power consistent with consumer and industry needs.

35

•

•

•

7.3 •

Accommodates a Wide Variety of Generation Options - a grid that allows and takes advantage of a wide variety of local and regional generation technologies (including green power). Fully Enables Electricity Markets - a grid that fully enables maturing electricity markets. Optimizes Asset Utilization - a grid that employs IT and monitoring technologies to continually optimize its capital assets while minimizing operations and maintenance costs (O&M).

Need for further work  Discuss the implied technologies and costs and potential deployment

36

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45

List of abbreviations

AER

All Electric Range

AT-PZEV

Advanced Technology Partial Zero Emissions Vehicle

BEV

Battery Electric Vehicle

CD

Charge Depleting

CS

Charge Sustaining

CV

Conventional Vehicle

DOD

Depth of Discharge (= 1- SOC)

EDV

Electric-Drive Vehicle

FCV

Fuel Cell Vehicle

HEV

Hybrid Electric Vehicle

ICE

Internal Combustion Engine

PHEV

Plug-in Hybrid Electric Vehicle

PVEV

PhotoVoltaic Electric Vehicle

SOC

State of Charge

SUV

Sport Utility Vehicle

TTW

Tank-To-Wheel

USABC

United States Advanced Battery Consortium

V2G

Vehicle-to-Grid

WTT

Well-To-Tank 

WTW

Well-To-Wheel

46

ANNEX I: List of expected PHEVs (non-exhaustive)

Manufacturer

Audi

Model

A1 Sportback

Category

Architecture

Fuel

Berline (sport)

AER (km)

Battery type

50100

Li-ion

Battery energy storage (kWh)

Vehicle cost (indicative)

2011

BYD Auto

BYD F3DM

Medium/big

Parallel

Gasoline

100

LiFePO 4

20

€1135014670

BYD Auto

BYD F6DM

Medium/big

Parallel

Gasoline

100

LiFePO 4

20

€1793821525

Chrysler

Chrysler 200 C EV

Medium/big

Series

Gasoline

64

Li-ion

27

Chrysler

Chrysler Jeep Wrangler EV

Medium/big

Series

64

Li-ion

Chrysler

Chrysler Town&Country

Minivans

Series

64

Li-ion

Chrysler

Chrysler Jeep Patriot EV

SUV

64

Li-ion

Fisker

Fisker Karma

80

Li-ion

22

Ford

Volvo V70

50

Li-ion

11.3

Ford

Escape

SUV

50

Li-ion

GM

Chevrolet Volt

GM

Opel Ampera Cadillac Converj Saturn Vue Green Line Blue-Will concept car Prius Golf VI TwinDrive

GM GM Hyundai Toyota VW

Berline (sport) Medium/big (break)

Series Diesel

Expected date

€55000

China (2008); 2011 in the EU China (2008) and 2010 in the US 2010 USA; 2013 EU 2010 USA; 2013 EU 2010 USA; 2013 EU 2010 USA; 2013 EU 2010 2012

Medium/big

SeriesParallel Series

Gasoline/E85

64

Li-ion

16

€28700

2010

Medium/big

Series

Gasoline

60

Li-ion

16

€35000

2011

Medium/big

Series

64

Li-ion

16

16

Li-ion

$40000

2011 (USA)

Gasoline

60

Li-ion

SUV Berline (sport) Medium/big

Split

Gasoline

50

Li-ion

Medium/big

Series

Diesel

50

Li-ion

47

2012 $48000 16

2010

ANNEX II: List of expected BEVs13 (non-exhaustive) Manufacturer

Model

Category

AER (km)

Battery type

Energy Storage (kWh)

BMW

Mini E

Small

240

Li-Ion

35 (28 usable)

BYD Auto

BYD e6 EV

Berline

400

LiFePO4

72

Chery Automobile

S18 EV

Small

150

Li-ion

40

Chrysler

Chrysler Dodge Circuit EV

Berline (sport)

241-322

Li-Ion

26

CODA Automotive

Coda EV

Berline

145-195

Li-ion

Daimler

Smart Fortwo Brabus Electric

Small

115

Fiat

Fiat-Fiorino Micro-Vett

Small Small Small/medium

128

Ford

Fiat E500 Fiat Palio Eléctric Focus EV

70-130 (depending on the model) 110

Berline

Mitsubishi

iMiEV

Small

160 140-160 (MY2006) (150)

NICE/Fiat

Micro-Vett e500

Small

Nissan

Nissan EV

Fiat Fiat

Pininfarina PSA Renault

Bluecar aka B0 Citroen C1 eléctrico (conversión) Fluence EV

Vehicle cost (indicative)

$14600

$45000

Li-Ion

22

€29900 (lowcost version)

Li-Ion

22

Aprox €27000

Ni-MH

Brasil 2011 in the US Japan (2009); EU and US (2010)

Li-Ion

16/20

120

Li-Ion

18

160

Li-Ion

Small

250

Li-MP+ supercapacitor

Small

112

€18882

$28000-30000

Berline

2011

Small (Kangoo)

100 (up to 150 soon)

Li-ion

15

Spyder

Berline (sport)

125 (80 km/h)

Li-Poly

16

€60000 ($83000)

Small

80

Li-Ion

Small

90

Li-Ion

Tata Motors

R1e EV Plug-in Stella concept Indica EV

Small

Li-Ion

Tesla Motors

Roadster

Berline (sport)

Li-Ion

56

$109000

Tesla Motors

Model S

Berline (sport)

200 360 (combined cycle) 257-483

Li-Ion

42-70

Th!nk

City EV

Small

180

Li-ion or zebra

28.3

Aprox €36000 Around €25000 in France

Toyota

FT-EV

Small (iQ)

80

ZENN

City Zenn

Small

400

Subaru

13

2010 mass production in Japan and US 2010 in Italy

be bop ZE

Rudolph Perfect Roadster Subaru

End 2009 (China) 2010 USA-2013 UE

€13000 (including 5000 subsidies)

Renault

Market introduction (target) Leasing Plan, NY, CA, London and New Jersey

Li-ion

See e.g. http://www.avem.fr/index.php?page=vep-elec

48

9

2010-2011

€13000-16000

2009 Japan

Aprox. €35000

2009-2010 2009 Available in US and Europe

2010 in the US

2010

European Commission JRC 54699 – Joint Research Centre – Institute for Prospective Technological Studies Title: Plug-in Hybrid and Battery-Electric Vehicles: State of the research and development and comparative analysis of energy and cost efficiency Authors: Françoise Nemry, Guillaume Leduc, Almudena Muñoz Babiano Luxembourg: Office for Official Publications of the European Communities 2009 Technical Note

Abstract This technical note is a first contribution from IPTS to a JRC more integrated assessment of future penetration pathways of new vehicles technologies in the EU27 market and of their impacts on energy security, GHG emissions and on the economy. The present report focuses on battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). It provides a general overview of the current state of the research and development about the concerned technologies and builds some first estimation regarding the fuel and electricity consumptions, and the costs of these new vehicle technologies in the short term and in the longer terms in view of their subsequent use when building prospective market penetration and policy scenarios.