车辆混合动力系统不确定性传播与参数优化

Uncertainty Propagation and Parameter Optimization of Power System in Hybrid Electric Vehicle

根据混合动力车辆的工作特性,对不确定下车辆混合动力系统参数优化的多学科设计优化方法进行研究。采用蒙特卡罗仿真估计车辆混合动力系统输入参数的不确定性对系统性能的影响;采用物理规划法构造系统性能目标的综合偏好函数和约束来满足实际需求与设计偏好;利用目标分流法对车辆混合动力系统的参数优化问题进行层次分解及协同优化。最终方案不仅使混合动力系统的功率匹配更加满足设计偏好,还使系统的设计参数达到最优配置。

According to the working characteristic of hybrid electric vehicle（HEV） in different conditions,the multidisciplinary design optimization（MDO） method in parameter optimization of power system of HEV under uncertainty was studied.To estimate the impact of uncertain input parameters on objectives of drive power system by performing the Monte Carlo simulation.The aggregate preference function of objectives and corresponding constraint equation were constructed to satisfy the designers’ preference and engineering design.The power system parameters were optimized by using analytical target cascading（ATC） method which could hierarchically decompose and collaboratively optimize the system.The results showed that the values of vehicle ’s performance and the power system design could be optimized currently.