Factors affecting electric vehicle energy consumption

Figures & data

Table 1 Default input parameters used for EV simulation.

Parameter	Default value
Vehicle mass (not including batteries)	1000 kg (2010 VW Golf weight 1314 kg, Volkswagen 2010) minus weight saved by swapping engine, exhaust and fuel tank for electric motor and possible light-weighting 314 kg)
Battery mass	300 kg
Coefficient of drag	0.25 (this is a low figure but has been achieved by the Toyota Prius/Audi A2 and Mercedes are aiming for < 0.2 within 5 years, Mercedes-Benz 2009)
Vehicle frontal area	1.8 m^2 (Ford Escort)
Percentage of energy recouped through braking	50% (this is thought to be the maximum that is practically achievable, Moeller 2002)
System efficiency	95% (allows for mechanical losses with single speed gearbox, Ehsani et al. 2005, Campanari et al. 2009)
Road incline	0°
Average power drawn by accessories	800 W (Rashid 2007)
Coefficient of rolling resistance	0.007 (this represents energy efficient tyres)
Density of air	1.25 kg/m^3 at an air temperature of ≈ 10°C
Tyres	175/65R14 having a radius of 0.3 m

Table 2 Energy consumption data for selected conventional sized EVs on the market.

Vehicle	Energy consumption (kWh/km)
Peugeot Berlingo Electric	0.22 (Lane 2006)
Electric Smart fortwo	0.15 (Carroll 2010)
i-MiEV	0.12 (Mitsubishi Motors 2011)
Toyota RAV4 EV	0.15 (over SAE J1634 cycle; Idaho National Laboratory 1998)

Table 3 Average performance and estimated costs of various battery technologies (Ehsani et al. 2005, Westbrook 2007, ThermoAnalytics 2010).

Battery type	Specific energy (Wh/kg)	Specific power (W/kg)	Number of cycles down to 80% DOD	Approximate current cell cost (£/kWh)	Estimated large-scale cell production cost (£/kWh)
Lead-acid	35	150	1000	70	40
Valve regulated lead-acid	50	250	1500	130	130
Nickel cadmium	50	150	1000	255	190
Nickel-metal hydride	80	200	1200+	200	160
Lithium-ion	120	250	1000+	300 (BatterySpace.com 2011)	130
Zinc–air	200	120	200	200	65

Figure 1 Effect of battery mass and type on vehicle range and cost.

Figure 2 Effect of battery mass and specific energy on range.

Figure 3 Effect of EV parameters on vehicle energy consumption.

Figure 4 Motor efficiency map with required motor outputs.

Table 4 Comparison of driving cycles (Ehsani et al. 2005, Kasseris and Heywood 2007).

	Driving cycle
	FTP urban	FTP highway	NEDC	US06
Average speed (kph)	27.9	79.3	33.5	77.5
Maximum speed (kph)	86.4	97.7	120	128.5
Fuel consumption for Toyota Camry 2.5 l (litre/100 km)	9.9	7.5	8.8	8.4

Table 5 Effect of driving cycle on energy consumption and range.

ECE-15 velocity multiple factor	Extrapolated 0–96.6 kph time (s)	Maximum acceleration (m/s)	Max. speed (kph)	Energy usage (kWh/km)	Range to 80% DOD (km)
0.5	100	0.49	25	0.172	163
0	50	0.97	50	0.142	196
1.5	33	1.46	75	0.159	174
2	25	1.94	100	0.195	140
2.5	20	2.43	125	0.241	111
Constant 48 kph	–	0	48	0.083	338
Constant 80 kph	–	0	80	0.120	232
Constant 113 kph	–	0	113	0.189	146

Table 6 Comparison of the energy consumption of different drivetrains (figures in parentheses indicate values for the most efficient vehicle in range).

Vehicles	Energy consumption per km (kWh)
Measured data
Average petrol Volkswagen Golf	0.53 (0.51)
Average petrol Ford Focus	0.60 (0.58)
Average diesel Volkswagen Golf	0.50 (0.38)
Average diesel Ford Focus	0.52 (0.43)
Toyota Prius Hybrid petrol/electric	0.35
Honda Civic Hybrid petrol/electric	0.41
Calculated data
EV using default values	0.14
EV with 4 kW accessory draw	0.24
EV over ECE-15 multiplied by 2.5	0.24
EV with combined worse effects of all parameters from Figure 3	0.23

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