Energy Management Strategy of Hybrid Electric Vehicle using Stochastic Dynamic Programming

This paper is concerned with the energy management strategy of hybrid electric vehicle using stochastic dynamic programming. The aim is the control strategy of the power distribution for hybrid electric vehicle powertrains to minimize fuel consumption while maintaining drivability. The fuel economy of hybrid electric vehicle is strongly influenced by power management control strategy. Rule-based control strategy is popular strategy thanks to its effectiveness in real-time implementation, but rule should be designed and efficiency of entire drive trains is not optimized. Dynamic programming, one of optimization-based control strategy presents outstanding performance, but cannot be used as real-time control strategy directly, since its non-causal property and drawback that global optimal solution can only be obtained for specific driving cycle. In this paper, stochastic dynamic programming is applied to parallel hybrid electric vehicle to optimize vehicle performance in average sense. The power demand of driver is represented by Markov process and an infinite horizon optimization problem is formulated. Based on result of stochastic dynamic programming, power split ratio map are optimized to achieve improved fuel economy. Control strategy is simulated on the several standard driving cycles to demonstrate fuel economy performance. Also, dynamic programming and rule-based control strategy are simulated to compare with.