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Flywheel motor topology was analyzed, and a main performance optimization model and stator/rotor core loss optimization model were provided. Then, an adaptive kriging surrogate model based on the MaxPro design (AKMMP) was used, improving the optimization precision and efficiency. Based on these preliminary outcomes, a stepwise optimization design method of flywheel motor based on AKMMP was proposed. The brief design process includes five steps: 1) initial structure of the flywheel motor: outer rotor, 16 poles/18 slots, double layer concentrated winding, inclined shoulder flat bottom slot, water cooling, and F grade insulation; 2) first step optimization: performance optimization using AKMMP to obtain the performance Pareto solution set; 3) according to the performance of a flywheel motor, selection of the suitable case from the performance Pareto solution set; 4) second step optimization: further optimization of the stator/rotor core loss for the case obtained before using AKMMP, and; 5) creation of the final optimization design structure. Then, complete the flywheel motor design by the stepwise optimization design method. Finally, the prototype of the flywheel motor was produced, and performance testing was performed.

An aero flywheel motor (AFM) is an integration of a starter, generator, and inertial flywheel on the traditional aero piston-engine (APE). When performing as a starter, the AFM is responsible for dragging the APE to a high speed (600-800 rpm) in a short time (0.2-0.4 s). In order to obtain better performance, two modifications are applied to the direct torque control (DTC) method. First, the switching table is modified by using only the positive voltage vectors. Second, a new low-pass filter (LPF) flux estimator is proposed to eliminate the initial flux error using the pulse width modulated (PWM) flux orientation method and the resistance estimation error by using real-time varying (RTV) equivalent resistance. Three DTC-based starting strategies are developed for the AFM, namely, the constant acceleration strategy (CAS), the constant torque strategy (CTS), and the modified constant current strategy (MCCS). The modified and traditional DTC methods are compared to the three starting strategies. The results show that the proposed switching table significantly reduces the switching frequency, and the proposed LPF flux estimator improves the convergence of the DTC method; in addition, the robustness against the resistance error is improved. The performances of the three starting strategies based on the modified DTC method are also compared. The results show that the MCCS significantly reduces the peak value of the battery current, thus reducing the capacity, weight, and size of the battery.

This paper proposes an efficient and accurate surrogate model, called adaptive Kriging model based on maximum projection (MaxPro) design (AKMMP), and establishes the design method by using the non-dominated sorting genetic algorithm with the elitism approach (NSGA-2) and AKMMP to optimize the mass and torque density as the performance parameters of flywheel motor with consideration of rotational inertia. The Pareto optimal solution set of flywheel motor is provided and used as the design border for the flywheel motor. The detailed design parameters are the armature diameter and axial length, rotor and stator split ratios, and permanent magnet width related to the mass and torque density. The brief optimization process includes five steps: A) getting the initial samples by MaxPro design; B) building the Kriging model based on the initial samples; C) optimization by NSGA-2 based on the Kriging model; D) selecting the corrected test point by the proposed sample strategy; and E) judging the convergence. The seven cases with different masses are analyzed, and the finite-element method is used to verify the optimization method.

The performance of flywheel motor is decided by the airgap flux density waveform. This paper establishes an efficient model to optimize the airgap flux density waveform and provides the Pareto optimal solutions, which give the design boundary of airgap flux density waveform for flywheel motor. The key elements of the structure of permanent magnet and the airgap are considered to optimize the sinusoidal distortion rate and the fundamental amplitude of the airgap flux density waveform. The brief optimization process is three steps: 1) sampling by maximum projection design; 2) building surrogate model by the Kriging method; and 3) multi-objective optimization by non-dominated sorting genetic algorithm with elitism approach (NSGA-2) based on the Kriging model. Then, the Pareto optimal solutions are obtained. The three cases optimized by different strategies are compared, and the optimization method is verified by finite-element method.

The flywheel motor is one of the best ways to improve the power-to-weight ratio of the compression ignition heavy fuel aircraft piston engine (CIHFAPE). In this paper, the influence of stator split ratio, rotor split ratio, armature diameter and axial length on the torque density of flywheel motor is studied in detail. An optimization design method of flywheel motor based on torque density is proposed, which combined with analytical method and finite element method. The local optimum design is obtained by optimizing the stator split ratio and rotor split ratio, and the overall optimal design is obtained by optimized armature diameter and axial length. Under a limited conditions, the torque density of the flywheel motor designed by this method is 8.05N m / kg, and the rotational inertia is 0.11kg·m2. The precision of the optimization design method is verified by FEM.