Abstract: A fast parameter matching method for hybrid energy storage system applied to electric vehicle is proposed, optimizing HESS parameters and corresponding energy management strategy simultaneously. In order to avoid computation burden/suboptimal problems when solving this optimization problem with dynamic programming(DP) method or evolutionary algorithms, convex optimization theory is applied to solve this problem. Firstly, nonlinear relationship of HESS model is approximated into linear relationship, then the objective function and constraints are converted to convex functions by introducing new variables; the original optimization problem is thus transformed into convex optimization problem, finally the problem is solved using Matlab/cvx toolbox. The same problem is solved using DP method and optimization results of both methods are compared:there are only 4% difference between optimization results, which means convex optimization ensures results to be global optimal; additionally, convex optimization shows favourable engineering application potential for its computation time never exceeds 100 s, which is far less than DP method. The optimization result shows that:battery pack life mileage is doubled by introducing an ultracpacitor pack with no more than 60 Wh, and convex optimization weights can be tuned to obtain desired HESS parameters rapidly.

Key words: convex optimization, energy management, hybrid energy storage system, parameter matching