Fast Evaluation of Driving Cycle Efficiency of Interior Permanent Magnet Synchronous Machines for Electric Vehicles Considering Step-Skewing

In this paper, a fast evaluation of efficiency map and driving cycle efficiency of interior permanent magnet synchronous machines (IPMSMs) for electric vehicles (EVs) is proposed. Several techniques are applied to speed up the simulation process, including the iron loss and AC Joule loss calculation...

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Bibliographic Details
Published in:IEEE transactions on industry applications 2024-05, Vol.60 (3), p.4396-4407
Main Authors: Cheng, Yuhang, Wang, Yawei, Ma, Jimin, Liu, Guanghua, Li, Dawei, Qu, Ronghai
Format: Article
Language:English
Subjects:
Buildings
Computer simulation
Core loss
Driving cycle efficiency
Efficiency
efficiency map
Electric vehicles
Evolutionary algorithms
Evolutionary computation
interior permanent magnet synchronous machines
Iron
Magnetic hysteresis
multi-objective optimization
Multiple objective analysis
Optimization
Permanent magnets
Phase current
Rotors
Simulation
Stators
step-skewing
Synchronous machines
Torque
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Summary:In this paper, a fast evaluation of efficiency map and driving cycle efficiency of interior permanent magnet synchronous machines (IPMSMs) for electric vehicles (EVs) is proposed. Several techniques are applied to speed up the simulation process, including the iron loss and AC Joule loss calculations via static and time-harmonic magnetic simulation, efficiency map building via surface-fit and driving cycle efficiency via finite element interpolation. Moreover, an equivalent phase current angle technique is used to imitate the step-skewed simulation. As a result, compared to the commercial software, the calculation time consumption of the efficiency map and driving cycle efficiency can be reduced by 99.4% and 98.1%, respectively. It shows a great potential for the fast evaluation of the IPMSM performances. Furthermore, this fast evaluation method is combined with differential evolution algorithm to carry out a multi-mode and multi-objective optimization on an IPMSM, which will be of great benefit for the determination of the optimal traction motors for EVs. Finally, a prototype of the optimal machine is manufactured and tested to validate the precision of proposed method. The experimental results show good agreement with the results obtained by the proposed method.
ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2024.3370093