Hybrid electric vehicle electric motors for optimum energy efficiency: A computationally efficient design

Dong Wei, Hongwen He and Jianfei Cao

Energy, 2020, vol. 203, issue C

Abstract: This paper proposes a new optimal design approach of a permanent magnet synchronous motor (PMSM) in hybrid electric vehicles (HEVs). It aims to solve the key research problem of how to find a viable and computationally efficient solution to achieve the maximum energy efficiency of the motor over the driving cycles. A one-dimensional analytical model is, firstly, built and validated to design the geometric parameters and calculate motor efficiency, maintaining high fidelity calculation with low computational cost. Then, by analyzing the motor energy distribution of the driving cycle, the energy efficiency is characterized by representative points, which can dramatically reduce the computation time during the optimal design. Leveraging by these points, the approximation model is presented to replace the PMSM optimization model to further reduce the computational cost. Finally, a combinatorial optimization algorithm is developed to return and characterize the PMSM optimal design in the studied scenario benefiting in the energy-loss reduction. The performance of the approach has been illustrated and verified with a HEV dynamics model. The results show that the optimal design approach can reduce the motor energy losses by 18.35% and improve the HEV fuel economy by 3.2% over the driving cycle compared with the initial design.

Keywords: Optimal design; Hybrid electric vehicle (HEV); Electric motors; Energy efficiency; Driving cycle (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220308860
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:203:y:2020:i:c:s0360544220308860

DOI: 10.1016/j.energy.2020.117779

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().