A stochastic power management strategy with skid avoidance for improving energy efficiency of in-wheel motor electric vehicles

Abstract

In this study, a stochastic power management strategy for in-wheel motor electric vehicles is proposed to reduce the energy consumption and increase the driving range, considering the unpredictable nature of the driving power demand. A stochastic dynamic programming approach, policy iteration algorithm, is used to create an infinite horizon problem formulation to calculate optimal power distribution policies for the vehicle. The developed stochastic dynamic programming strategy distributes the demanded power, P_dem between the front and rear in-wheel motors by considering states of the vehicle, including the vehicle speed and the front and the rear wheels’ slip ratios. In addition, a skid avoidance rule is added to the power management strategy to maintain the wheels’ slip ratios within the desired values. Undesirable slip ratios cause poor brake and traction control performances and therefore should be avoided. The resulting strategy consists of a time-invariant, rule-based controller which is fast enough for real time implementations, and additionally, it is not expensive to be launched since the future power demand is approximated without a need to vehicle communication systems or telemetric capability. A high-fidelity model of an in-wheel motor electric vehicle is developed in the Autonomie/Simulink environment for evaluating the proposed strategy. The simulation results show that the proposed stochastic dynamic programming strategy is more efficient in comparison to some benchmark strategies, such as an equal power distribution and generalized rule-based dynamic programming. The simulation results of different driving scenarios for the considered in-wheel motor electric vehicle show the proposed power management strategy leads to 3% energy consumption reduction in average, at no additional cost. If the resulting energy savings is considered for the total annual trips for the vehicle and also the total number of electric vehicles in the country, the proposed power management strategy has a significant impact.

Keywords

Battery electric vehicle in-wheel motor electric vehicle power management strategy stochastic programming Markov processes dynamic programming

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