Real-time model-based loss minimisation control for electric vehicle drives

Abstract

Environmental concern and the opportunity for commercial gain are two factors driving the expansion of the electric vehicle (EV) market. Due to the limitations of current battery technology, the efficiency of the traction drive, which includes the electric motor and power electronic converter, is of prime importance. Whilst electric machines utilising permanent magnets (PMs) are popular due to their high energy density, industry concerns about the security of supply have led to interest in magnet-free solutions. Induction machines (IMs) offer such an option. Control of IMs is a mature but complex field. Many techniques for optimising the efficiency of the drive system have been proposed. The vast majority of these methods involve an analytical study of the system to reveal relationships between the controlled variable and efficiency, allowing the latter to be optimised. This inevitably involves simplifications of the problem to arrive at a practically-implementable control scheme. What has not been investigated is real-time calculation of the system losses in order to optimise the efficiency, and the work presented in this thesis attempts to achieve this. The conventional control scheme is examined and a new structure implemented where a model of the system loss is able to directly influence the switching action of the inverter, thus reducing loss. The need to maintain performance alongside loss minimisation is recognised and a cost function-based solution proposed. The validation of this structure is performed both in simulation and on a practical test platform. A model of the principle losses in the drive system is derived, taking into account the processing power typically available for this application, and implemented in the structure outlined. The effect of the new control scheme on efficiency is investigated and results show gains of up to 3%-points are achievable under certain conditions.