System Cost Reduction by Electric Powertrain Design Optimization

The presented optimization method supports early system design of electric axle drives (eDrives) for battery and hybrid electric vehicles. The multi-criteria design problem of finding the best suitable solutions regarding performance, efficiency, package and costs is addressed with a sophisticated multi-objective optimization method. The overall system costs are reduced by including common-part considerations for purchased parts, demonstrated on the example of bearings. Two approaches are compared: the implicit approach relies on an extended cost model that covers a quantity-dependent cost reduction effect. The explicit approach directly minimizes the number of unique parts in the system. Both approaches are compared and the effect on the optimal system solution is discussed for a case study, which shows significant cost reduction potential.