Integrated Starter Generator: The Need for an Optimal Design and Control Approach. Application to a Permanent Magnet Machine

This paper proposes to apply optimal approaches to the design and control of a highly constrained electric machine. The developed approach is applied on a permanent-magnet integrated starter generator (ISG) but may be applied on any high-constrained electric machine. One of the main problems in the use of optimal approaches is the accuracy of the models used by the optimizer. In our approach, we propose to proceed in two steps. 1) Optimal design: the model is purely analytic, and some phenomena are neglected (cross saturation). Under these conditions, the electric machine design is optimal for a limited number of constraints. The design model uses a classic uncoupled d,q reluctant circuit model (with saturation taken into account). 2) Optimal control: once the machine is calculated, the design constraints are validated by a finite-element (FE) method. The FE method allows to use a more accurate model to compute optimal currents for the control on the whole torque-speed plane. In our case, we use FE results to model the cross-saturation phenomenon. The optimizer is common to both cases and is a classic commercial sequential quadratic programming algorithm. This model is validated by experimental results based on an ISG. This paper shows that optimal design and control allows for permanent-magnet machine, high flux-weakening mode, and high-efficiency operations even for a simple machine structure     

Shape sensitivity analysis of magnetic forces

This paper presents a shape sensitivity analysis of magnetic forces evaluated using the Maxwell stress tensor and the finite element method. The formulation is based upon a discrete approach which takes the analytical derivatives of the finite element equations with respect to the shape variables and also on the adjoint variable method in order to carry out the derivation procedure. Sensitivity analysis is developed in the context of the axisymmetrical nonlinear magnetostatic field problem with a modified magnetic vector potential as state variable. Numerical results are presented to validate this methodology. Shape sensitivity analysis is then applied to the optimization of the force-displacement characteristic of a linear actuator. A sequential quadratic programming method is used in the optimization process