基于凸优化的车载复合电源参数匹配  

Parameter Matching of On-board Hybrid Energy Storage System Based on Convex Optimization Method

作　　者：宋传学[1] 周放[1] 肖峰[1] 常成[1] 邵玉龙 

机构地区：[1]吉林大学汽车仿真与控制国家重点实验室,长春130022

出　　处：《机械工程学报》2017年第16期44-51,共8页Journal of Mechanical Engineering

基　　金：吉林省重点科技攻关资助项目(20150204017GX)

摘　　要：提出一种电动汽车复合电源参数快速匹配方法,对复合电源参数和能量管理策略同时进行优化。为避免动态规划或者进化算法在求解此类优化问题时出现的计算负担大或结果次优的问题,应用凸优化原理对优化问题进行求解。对复合电源模型进行线性近似,并引入新变量对优化问题中的目标函数和约束进行转换,将优化问题转化为凸优化问题,最后应用Matlab/cvx工具箱进行求解。应用动态规划求解此优化问题并对比优化结果:凸优化和动态规划结果相差在4%以内,凸优化保证了全局最优;凸优化耗时不超过100 s,明显优于动态规划,有良好的工程应用潜力。凸优化结果表明:通过增加最大不超过60 W·h的超级电容组能够延长电池组一倍的寿命里程,改变凸优化问题的权重可以快速获取所需参数。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.

关 键 词：复合电源 参数匹配 凸优化 能量管理 

分 类 号：U461[机械工程—车辆工程]