Date of Award

1-1-2019

Publication Type

Doctoral Thesis

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

Keywords

EV, LPTN, Modelling, Motor, Thermal, Traction

Supervisor

Narayan Kar

Rights

info:eu-repo/semantics/embargoedAccess

Abstract

This thesis investigates thermal modelling of traction motors for thermal characterization and protection in electric vehicle application. The requirements for traction motor characteristics include high power density; high torque at low speed for starting and climbing; high power at high speed for cruising; wide speed range; a fast torque response; high efficiency over wide torque and speed ranges and high reliability. High torque and power density requirements in traction motors mean increasing current and consequently, higher temperature rise in the motor. When the temperature of the winding and magnet in traction motors exceed permissible thermal limit frequently due to lack of proper understanding and managing of the thermal conditions it will have a short-term and a long term impacts on the motor operation. In the short-term, it will never be able to produce required torque and power for standard driving conditions of electric vehicle. In the long-term, it will have the detrimental effects on the life of insulation material and consequently, it will cause permanent insulation breakdown and on the other hand, demagnetization due to higher temperature will cause a permanent damage to the motor. Hence, it is extremely important to predict temperature rise in the motor accurately and regulate liquid cooling accordingly so that the motor does not fail to produce required torque and power for any driving conditions. This research work proposes a higher order lumped parameter thermal network (LPTN) model to determine a comprehensive thermal characterization of the traction motors. Such characterization predicts the temperature of the winding, magnet and other parts of the motor. The proposed model is capable of taking inputs dynamically of motor operating parameters in electric vehicle and generate a motor loss model that feeds loss results into LPTN thermal model to predict motor temperature. The proposed model investigates cooling requirements to the motor so that the motor continues to produce the rated torque and power. The LPTN model results are validated through thermal tests on a copper rotor induction motor (CRIM) and an interior permanent magnet synchronous motor (IPMSM) in the laboratory

Download

Share

COinS