Concurrent Design Optimization of Shared Powertrain Modules in a Family of Electric Vehicles

We present a concurrent optimization framework to design shared modular powertrain components for a family of battery electric vehicles, whereby the modules' sizes are jointly-optimized to minimize the family Total Cost of Ownership (TCO). As opposed to individually-tailoring the components, our approach can significantly reduce production costs due to the higher volumes of the same item. We instantiate a bi-level nested framework consisting of an inner convex optimization routine, which jointly optimizes the modules' sizes and the powertrain operation for given driving cycles and modules' multiplicities, and an outer loop comparing each configuration to identify the minimum-TCO family co-design solution with global optimality guarantees. Finally, we showcase our framework on a case study for the Tesla family in a benchmark design problem, considering the Model S, Model 3, Model X, and Model Y. Our results show that, compared to an individually tailored design, the application of our concurrent design optimization framework achieves a significant reduction of acquisition price for a minimal increase in operational costs, ultimately lowering the family TCO in the benchmark design problem by 3.5%. Moreover, in a sensitivity study on the market conditions considered, our concurrent design optimization methodology can reduce the TCO by up to 17%.