混合动力系统多目标优化的混合度参数匹配方法
Multi-objective optimization of component sizing of hybrid electric powertrain based on degree of hybridization

以一款并联式混合动力系统为研究对象，提出一种集动力性、 经济性、 排放性于一体的多目标优化的混合度参数匹配方法. 以整车各性能指标为价值函数，选定混合度为匹配设计变量，采用粒子群优化算法进行优化，获得不同权重系数下的优化混合度. 同时权衡部件成本，进而选定最佳混合度进行参数匹配，并运用Advisor仿真软件进行验证. 结果表明，与优化前相比，最高车速提高了19.7%，百公里油耗降低了9.8%，排放量降低了19.8%.
For a kind of parallel hybrid electric powertrain，a multi-objective optimization technique based on the vehicle performance，fuel economy and emissions is proposed，in which the optimizations on degree of hybridization（DOH) is concurrently performed. The indexs of vehicle performance，fuel economy and emissions are constructed as the cost function，and the DOH is selected to match the design variables，which are optimized by using the particle swarm optimization(PSO). The DOH is obtained under different weight coefficients and the components cost is simultaneously balanced to select the optimal DOH which are verified by advisor. The results show that maximum speed increases by 19.7%，the fuel consumption and CO reduces by 9.8% and 19.8% compared with the non-optimized powertrain