A multi-objective power flow optimization control strategy for a power split plug-in hybrid electric vehicle using game theory

Power flow optimization control, which governs the energy flow among engine, battery, and motor, plays a very important role in plug-in hybrid electric vehicles (PHEVs). Its performance directly affects the fuel economy of PHEVs. For the purpose of improving fuel economy, the electric system including battery and motor will be frequently scheduled, which would affect battery life. Therefore, a multi-objective optimization mechanism taking fuel economy and battery life into account is necessary, which is also a research focus in field of hybrid vehicles. Motivated by this issue, this paper proposes a multi-objective power flow optimization control strategy for a power split PHEV using game theory. Firstly, since the demand power of driver which is necessary for the power flow optimization control, cannot be known in advance, the demand power of driver can be modelled using a Markov chain to obtain predicted demand power. Secondly, based on the predicted demand power, the multi-objective optimization control problem is transformed into a game problem. A novel non-cooperative game model between engine and battery is established, and the benefit function with fuel economy and battery life as the optimization objective is proposed. Thirdly, under the premise of satisfying various constraints, the participants of the above game maximize their own benefit function to obtain the Nash equilibrium, which comprises of optimal power split scheme. Finally, the proposed strategy is verified compared with two baseline strategies, and results show that the proposed strategy can reduce equivalent fuel consumption by about 15% compared with baseline strategy 1, and achieve similar fuel economy while greatly extend battery life simultaneously compared with baseline strategy 2.