Weight optimisation of a surface mount permanent magnet synchronous motor using genetic algorithms and a combined electromagnetic-thermal co-simulation environment

Hamiti, Tahar; Gerada, Chris; Rottach, M.

doi:10.1109/ecce.2011.6063964

Cited by 15 publications

(7 citation statements)

References 5 publications

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“…Lei's team established a model that can improve the motor's dynamic performance by using explicit constraints on multi-physics models, an integrated approach to minimize size, energy consumption, and torque constraints, and proposing new energy management strategies. Weight optimization, size, and topology optimization of permanent magnet synchronous motors (PMSM), inwheel active motor suspension control systems with sprung mass changes, actuator failures and control input constraints, and vibration and noise issues involved in in-wheel motors developed another model that optimizes motor weight and powertrain vibration are all aimed to improve ride comfort [5][6][7][8][9][10][11][12][13]. Riding quality and dynamic performance significantly affect the vehicle's energy consumption.…”

Section: Pure Electric Vehiclementioning

confidence: 99%

A review of methods to improve power transmission for energy efficiency of both electric and hybrid vehicle

Shi,

Zhao,

Wang

et al. 2023

ACE

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In recent years, many optimization methods have been raised to deal with the fuel and cost efficiency problems of the new generation cars. This study reviews two primary optimization methods, one for pure electric cars and one for hybrid vehicles, with detailed explanations. For electric vehicles, methods for designing electric powertrains that are energy efficient while sustaining vehicle dynamics and ride quality are discussed. The three characteristics of energy consumption, dynamic performance, and ride comfort are optimized using modeling, and the final optimization method is determined, which can achieve a 93.5% improvement in lightweight and a 92% improvement in power transmission. Four standard powertrain transmissions are mentioned for hybrid vehicles with advantages and limitations. The most promising multimode information is selected to work with a single EM instead of the dual EMs that conventional hybrid cars contain. The simulation results of the single-EM HEV with the MMT model and its comparison test with the "THS II-LIke'' vehicle, holding the same parameters except having dual EMs, show the well-performance of this method in energy loss. In the end, a more efficient engine, the Atkinson engine, for hybrid vehicles is illustrated to substitute the traditional otto cycle engine.

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Section: Pure Electric Vehiclementioning

confidence: 99%

A review of methods to improve power transmission for energy efficiency of both electric and hybrid vehicle

Shi,

Zhao,

Wang

et al. 2023

ACE

View full text Add to dashboard Cite

show abstract

“…Taking the mass of the motor as the target, the optimization design of the motor was completed using a genetic algorithm but, during the optimization process, the influence that the change in the motor structure has on the magnetic distribution was not considered. Hamiti et al 26 utilized the minimum mass of the motor as the goal, and the highest winding temperature and the mean square root value of the motor torque as the constraint conditions. By using a genetic algorithm, a lightweight design of the motor was carried out.…”

Section: Introductionmentioning

confidence: 99%

Lightweight design of an in-wheel motor using the hybrid optimization method

Luo

Tan

2013

Proceedings of the Institution of Mechanical Engineers, Part D:

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An increase in the unsprung mass is a critical issue for an electric vehicle driven by an in-wheel motor. The mass increase will cause the ride quality and comfort to deteriorate. To decrease the unsprung mass, a hybrid lightweight design method including size optimization and topology optimization is employed for the in-wheel motor. The two optimizations are carried out in sequence. First, the finite element method, the response surface method and the particle swarm optimization algorithm are employed in the size optimization design of the in-wheel motor. After this step, the mass of the in-wheel motor is reduced to 2.7448 kg, while its rated torque and losses are almost unchanged. Second, according to the above optimization results, topology optimization using the method of variable density is employed for the supporting frame of the stator of the in-wheel motor, which is the non-magnetic area. The material which is grade 45 steel is analysed. The optimization results show that, after optimization and treatment, the mass of the supporting frame is reduced to 1.069 kg, i.e. 63.11% lighter than before. Then, structural strength verification is carried out. Considering the above two optimization steps synthetically, the total mass of the in-wheel motor with a grade 45 steel supporting frame is reduced by 3.5547 kg, which means that it is 13.623% lighter than the original structure. Calculation of the transient torque and losses show that, after optimization, the total loss is reduced by 1.87%, and the torque by only 1.8%. Therefore, the hybrid optimization method studied in this paper works well for the lightweight design of an in-wheel motor.

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“…Evolutionary Algorithms, including GAs, are examples of direct optimization techniques that are able to find the area of the global minimum. GA have been widely used in optimization of electrical machine design [3], [6], [7], however, other evolutionary algorithms, like Immune Algorithms, Evolution Strategy, Differential Evolution [8], [9] and Particle Swarm Optimization [10] also show good results. In many cases, a hybrid solution is employed, where an Evolutionary Algorithm is used to find the area of the global minimum, and a local search algorithm is used to find the precise location of the minimum [4], [11], [12].…”

Section: B Previous Workmentioning

confidence: 99%

Gradient based optimization of Permanent Magnet generator design for a tidal turbine

Røkke

2014

2014 International Conference on Electrical Machines (ICEM)

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Abstract-An optimization of an analytical problem with nine variables is executed to find the optimal Permanent Magnet(PM) generator for a tidal turbine. A gradient based solver is used to find the minimum cost of active materials for the given design specifications. The MATLAB function fmincon is used, and the possible minimization algorithms available for this function are compared. As these solvers are only able to find a local minimum, a search is performed trying to find other minimas, both using a MultiStart procedure and using a Genetic Algorithm (GA). Losses are calculated for windings, stator laminations and rotor magnets and solid steel, and a constraint is put on efficiency. The cost effect of varying this constraint is investigated. Optimizations are done with both weight and material cost as objective function, and the different resulting designs are presented.

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Weight optimisation of a surface mount permanent magnet synchronous motor using genetic algorithms and a combined electromagnetic-thermal co-simulation environment

Cited by 15 publications

References 5 publications

A review of methods to improve power transmission for energy efficiency of both electric and hybrid vehicle

A review of methods to improve power transmission for energy efficiency of both electric and hybrid vehicle

Lightweight design of an in-wheel motor using the hybrid optimization method

Gradient based optimization of Permanent Magnet generator design for a tidal turbine

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