  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%.
