Multi-objective optimization research on the start condition for a parallel hybrid electric vehicle

One of the major issues for Parallel Hybrid Electric Vehicle (Parallel HEV) powertrain is the torsional vibration in the process of start condition, which is unavoidable. This article targets at reducing the damage caused by the torsional vibration with the method of Multi-Objective Optimization (MOO). The dynamic model of the parallel HEV powertrain is established by lumped mass method. Five design variables are selected from 19 parameters by the process of Design of Experiment (DOE), and are optimized by multi-objective downhill simplex optimization algorithm. Pareto Frontier is used to describe the relationship between the two objective functions, and one of the optimization data serves as the basics data for the powertrain modification. Finally, the results of optimization before and after optimization are compared by the test bench. Experimental results under the start condition show that the maximum torque of the optimized powertrain is decreased within the safe range, and the problem of shaft breaking on the originally powertrain is solved.