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In view of the optimization of E-REV’s powertrain parameter matching, a linear weighted multi-objective genetic algorithm was proposed based on the completion of powertrain parameter matching and performance simulation, in which parameters of drive motor, battery and engine were optimized with the targets of manufacturing costs, fuel consumption and acceleration time. Results showed that the vehicle’s dynamic and economic performance has been further improved, and manufacturing costs was reduced, which played a guiding significance on E-REV’s production in the market.