Controlling cabin heating to improve range and battery lifetime of electric vehicles

Abstract

Short range remains a major disadvantage of battery electric vehicles compared to vehicles that have combustion engines. Range reductions also result from low ambient temperatures and from battery aging. By varying power of the heating system depending on the highly fluctuating propulsion power and using electrothermal recuperation, range losses can be minimized. This paper focuses on the development and comparison of strategies to control the vehicle's heating circuit. Rule-based, fuzzy logic, and optimization-based strategies are designed and implemented in a validated BMW i3 simulation model. The results show that fuzzy logic leads to the greatest improvement of range and battery lifetime. Compared to the standard strategy, range can be increased by 14% at −10 °C and by 6.5% at 0 °C. The current throughput during recuperation is reduced the most by a rule-based strategy that prioritizes the heater. For discharging, fuzzy logic can reduce the current throughput by a maximum of 11%, which leads to a capacity fade reduction of 4.3%. Since air mass is controlled separately, the cabin temperature remains almost constant, thus maintaining the comfort of the user. • Heater power control adaptive to drive power increases range and battery lifetime. • Energy management concepts: Rule-based, Fuzzy Logic, and Optimization. • Validated BMW i3 model combines longitudinal dynamics, battery and coolant circuit. • Simple strategies show the best results and offer in-vehicle implementation. • At 0 °C, range can be increased by 6.5%, battery aging reduced by 2.1%.