Lithium battery has been widely utilized in electric vehicles as the energy storage system. However, Lithium battery suffers from the shortages of relatively low service time and high system cost, which induces the application of hybrid energy storage system (HESS), consisting of battery and supercapacitor. This paper proposes a joint optimization method of parameter matching and energy management for semi-active hybrid energy storage system utilized in electric vehicles. Based on Xi’an EV urban driving cycle, taking the prolong battery life as performance index, Dynamic Programming method is utilized to obtain the global optimal energy distribution. Based on the analyzing of global optimal results, the logical threshold energy control strategy can be built and the parameters of logical threshold control algorithm are taken as the joint optimization parameters. Together with the parameters of battery pack and supercapacitor pack, the multi-objective optimization problem is established and the optimization goal is to simultaneously minimize the replacement cost of HESS and the total energy consumption of HESS under specific cycle conditions. The improved ant lion optimization is used to solve this multi-objective optimization problem, which combines the ant lion optimization algorithm, chaotic mapping theory and particle swarm optimization together. The optimal HESS parameters have been obtained and the simulations results show that the battery service life can be prolonged by 20% by adding supercapacitors within acceptable increase of system cost.

CICTP