Energy Management Strategy based on Dynamic Programming Considering Engine Dynamic Operating Conditions Optimization

It is known that the hybrid vehicle energy management strategy based on dynamic programming (DP) can be used as a reference for other strategies. However, usually only fuel consumption of hybrid vehicles is focused on and dynamic conditions of engines are ignored. This research considers a plug-in hybrid electric vehicle as an object, a mathematical model of the vehicle and its energy management strategy based on dynamic programming are developed. The cost function of dynamic programming proposed in this paper not only pays attention to the fuel consumption of the vehicle, but also optimizes the engine start-stop state change and engine speed and torque fluctuation, thus ensuring the engine to work efficiently and have the potential of improving the emission performance. At the same time, entropy-weight method is introduced to determine the weight coefficients of the cost function, so that the determination process is separated from the subjective judgment and is closely linked with objective driving conditions. In addition, aiming at further improvement of DP optimization result when a lager discretization interval is selected for better real-time performance, a method for power deviation compensation is proposed. The simulation results show that the DP based energy management strategy considering the optimization of engine dynamic operating conditions has a small increase in fuel consumption compared with the traditional DP-based strategy, but it can significantly reduce the dynamic operating conditions of the engine and reduce the fluctuation of engine speed and torque and the frequency of engine start-stop.