To improve the operational performance of electric construction machinery, accelerate industry electrification, and reduce carbon emissions from non-road mobile equipment, a powertrain optimization design method considering manufacturing cost is proposed. The pure electric wheel loader is selected as the research object, and suitable components are first identified using the fuzzy TOPSIS method. Then, operating costs under customer demand conditions, power performance under loader turnaround conditions, and narrowly defined manufacturing costs are simultaneously optimized using an improved multi-objective Jellyfish search algorithm. Finally, the proposed method is verified on a Matlab/Simulink platform. Results show that the improved algorithm outperforms benchmark approaches. Motor efficiency increases by 0.214%, 0.190%, and 0.150% under different working conditions; the acceleration time from 0 to maximum speed is decreased by1.798 s, 2.231 s, and 1.006 s; and manufacturing cost is reduced by 3.129%, 5.043%, and 3.946%. Overall, both power performance and operational comfort are significantly enhanced.