Review of Electrical Motor Drives for Electric Vehicle Applications

Abstract

EVs (Electric Vehicles) have been rejuvenated over the last decades while the motor drive technologies are still evolving. This paper provides a review of electrical motor drive technologies used in EV applications, with a performance comparison of candidate machines and their drive topologies. EV applications demand high efficiency, high torque density, high reliability, and wide speed range while reducing weight, complexity, total costs and environmental impact. In the literature, DC (Direct Current) motors, IMs (Induction Motors) and PM (Permanent Magnet) motors can be generally found in marketplace whilst RMs (Reluctance Motors) have been researched for some time and are nearing commercial availability. This paper evaluates the performance of these four main types of electrical motor drives for EV propulsion applications using analytical methods. PM motors may offer the best performance in terms of torque density and compactness but the cost is the highest (primarily dominated by rare-earth permanent magnets), limiting their widespread application in mass production EVs. DC motors have their own merits but suffer from limited power density and necessity for maintenance. Induction motor drives are a mature and proven technology. In particular, squirrel-cage IMs are robust, reliable and inexpensive, striking a balance between system cost and complexity, power density and extended speed range. Reluctance motors can provide a good torque density and cost effective EV drive solutions. Their drawbacks can also be overcome by the use of power electronic converters and advanced control strategies. Induction and reluctance motor drives are well suited for cost sensitive mass production EV applications. Looking to the future, increased hybridization may be a way forward in industry which combines attractive features of different electrical machines and control algorithms and still offer much promise in performance and total cost. At last, reliability study on EVs requires historical information and driving patterns, demanding research expertise in eco-sociology, human behaviors as well as human-machine interface.