Abstract
In this work, we propose an iterative method to find the global solution of the energy management problem, which is defined as finding the minimum overall fuel consumption for a known drive cycle by managing the energy flow through the engine, the motor/generator and the battery feasibly. Finding the optimal solution to this problem while meeting the hard constraints such as meeting the expected level of the battery energy at the end of the journey (end-charge sustenance) is a challenging task. However, we demonstrate how an iterative procedure inspired by hill-climbing heuristic can solve this problem by a properly formulated objective function and a feasible solution evolving method. The proposed hill-climbing energy management strategy (HCEMS) starts with a feasible initial solution, which is evolved towards the final solution always in the direction of solution improvement. The objective function consists of the actual fuel consumption, a penalty to reduce the final deviation of the battery energy and a penalty to reduce frequent stopping and starting of the engine. We evaluate HCEMS with respect to another two existing energy management techniques dynamic programming (DP) and equivalent consumption minimization strategy (ECMS). Fuel consumption solutions of the HCEMS are nearly as good as DP. Moreover, HCEMS also requires very low computational cost compared to DP. HCEMS always performs better than ECMS in terms of fuel consumption and achieving the end-charge sustenance. Moreover, HCEMS can also improve poor solutions of other methods by taking them as initial solutions.
Keywords: Hybrid Electric Vehicles, Energy Management Strategy, Hill-Climbing Heuristics, Dynamic Programming, Equivalent Consumption Minimization Strategy.