For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.

中文翻译：

---

基于需求的增程式电动汽车动力系统参数匹配与优化

对于增程式电动汽车关键技术的研究，首先要解决的问题是增程式电动汽车动力和传动系统的参数匹配和效率优化。增程式电动汽车动力与传动系统参数匹配与优化是多目标优化问题。多目标优化问题的评价和分析应该是相互独立和平衡的。以保证汽车综合性能为目的，提出了一种增程式电动汽车动力与传动系统的参数匹配与优化方法。第一的，建立增程式电动汽车质量屋模型，根据市场需求而非经验确定汽车性能指标的权重系数。基于Matlab-Simulink和AVL-Cruise建立的联合仿真控制模型，进行40组正交试验，分析特征参数的敏感性，探索整车性能指标间的耦合规律，明确整车性能指标之间的耦合规律参数匹配和优化的入口点。仿真结果表明，特征参数不仅对整车性能指标有显着影响，而且还具有耦合作用。方差分析表明，各种因素的最优水平组合仅受范围的限制。然后，基于上述灵敏度分析结果，选择粒子群优化算法对增程式电动汽车动力及传动系统参数进行优化。研究表明，将增程式电动汽车动力及传动系统与更小容量的电池和“中型”辅助动力装置相匹配，更高效、更合理，可以获得足够的动力性能、更低的采购成本、更长的行驶时间。范围和更少的能源消耗。最后，对基于距离的分析与基于粒子群优化的分析进行了对比仿真，仿真结果表明优化后的设计参数方案能够显着提高整车的技术指标。