Coupled Electromagnetic-Thermal Analysis for Predicting Traction Motor Characteristics According to Electric Vehicle Driving Cycle

• Published in: IEEE transactions on vehicular technology Vol. 70; no. 5; pp. 4262 - 4272
• Main Authors: Hwang, Sung-Woo, Ryu, Jun-Yeol, Chin, Jun-Woo, Park, Soo-Hwan, Kim, Dae-Kee, Lim, Myung-Seop
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Circuits; Coupled analysis; driving cycle; Eigenvalues; Eigenvectors; electric vehicle; Electric vehicles; Electromagnetics; Finite element method; Heat sources; Iterative methods; Light duty vehicles; Lookup tables; lumped parameter thermal network; Mathematical analysis; Operating temperature; Permanent magnet motors; Process parameters; Synchronous motors; Table lookup; Temperature distribution; Thermal analysis; Thermodynamic properties; traction motor; Traction motors
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2021.3071943

The accuracy of motor characteristics prediction according to driving cycle can be improved by taking temperature change of motor into account. From this point of view, this paper proposes a fast and accurate coupled analysis method. To calculate motor circuit parameters, electromagnetic finite element analysis (FEA) is used. The proposed method consists of two stages to exclude the time consuming FEA from repetitive process. In pre-process stage, the circuit parameters are stored as look-up tables (LUTs) considering motor temperature. Further, a technique that allows reducing the number of analyses is developed to consider a wide operating temperature range with less time consumption. In main process stage, the torque and voltage equations are solved using the circuit parameter LUTs. Among the solved motor characteristics, losses are applied to lumped parameter thermal network (LPTN) as heat sources to figure out thermal characteristics. Here, techniques including loss separation and thermal parameter tuning are introduced to improve both accuracy and speed of the LPTN. Since the computation of the characteristic equations and LPTN are fast, the iterative analysis at entire time steps of the driving cycle is facilitated. An example of the proposed method is presented using worldwide harmonized light vehicle test procedure (WLTP). Thereafter, the effectiveness of the method is discussed by comparison with conventional methods. Finally, the experimental verifications are conducted to validate the electromagnetic FEA and LPTN used in this study.