Magnetic FEA Direct Optimization of High-Power Density, Halbach Array Permanent Magnet Electric Motors

Abstract

Hybrid electric aero-propulsion requires high power-density electric motors. The use of a constrained optimization method with the finite element analysis (FEA) is the best way to design these motors and to find the best solutions which maximize the power density. This makes it possible to take into account all the details of the geometry as well as the non-linear characteristics of magnetic materials, the conductive material and the current control strategy. Simulations were performed with a time stepping magnetodynamic solver while taking account the rotor movement and the stator winding was connected by an external electrical circuit. This study describes the magnetic FEA direct optimization approach for the design of Halbach array permanent magnet synchronous motors (PMSMs) and its advantages. An acceptable compromise between precision and computation time to estimate the electromagnetic torque, iron losses and eddy current losses was found. The finite element simulation was paired with analytical models to compute stress on the retaining sleeve, aerodynamic losses, and copper losses. This type of design procedure can be used to find the best machine configurations and establish design rules based on the specifications and materials selected. As an example, optimization results of PM motors minimizing total losses for a 150-kW application are presented for given speeds in the 2000 rpm to 50,000 rpm range. We compare different numbers of poles and power density between 5 kW/kg and 30 kW/kg. The choice of the number of poles is discussed in the function of the motor nominal speed and targeted power density as well as the compromise between iron losses and copper losses. In addition, the interest of having the current-control strategy as an optimization variable to generate a small amount of flux weakening is clearly shown.

Geometric design of electric motors using adjoint-based shape optimization

“…Objective functions are selected to be any combination of high-level outputs significant in overall motor operation and design. Examples include torque (Parasiliti et al, 2012), output power (Di Noia et al, 2020), efficiency (Idir et al, 1998), total power losses (Grenier et al, 2021) and motor mass (Parasiliti et al, 2012;Di Noia et al, 2020). Coupling between these parameters also motivates multiobjective design problems, aimed at optimizing the geometry for a combination of these states (Parasiliti et al, 2012;Di Noia et al, 2020).…”

Analytical Modeling of Magnetic Field Distribution at No Load for Surface Mounted Permanent Magnet Machines

“…On the other side, the method shows the weak points of assuming unity relative recoil permeability and neglect saturation. However, modern SPM machines are usually equipped with PM materials with pu recoil permeability typically around 1.09 [25][26][27], so quite close to vacuum permeability. Moreover, it is possible to show that the actual air-gap flux density distribution taking into account saturation can be obtained from the unsaturated one, multiplied by suitably calculated saturation correcting factors.…”

Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor

“…The FEM is the best way to design these motors and find the best solutions. In [17], Halbach PMs are directly optimized by the finite element method (FEM). Due to the complex three-dimensional magnetic circuit structure of the AFPM motor, it requires a very long time to complete an electromagnetic simulation.…”