Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

• An implicit constrained multi-physics model is built for sizing a motor wheel.
• Vehicle dynamic performances are applied as implicit constraints for nonlinear system.
• An efficient novel optimization is proposed to explore the constrained design space.
• The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics.
• Influences of implicit constraints on vehicle performances are compared and analyzed.

In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals.