Loss minimisation of induction motor-driven electric vehicle using teamwork optimisation. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Sahoo, Anjan Kumar; Jena, Ranjan K.
• Is Part Of: International journal of ambient energy. Volume 43:Issue 1(2022)
• Page Start: 8123
• Page End: 8134
• Publication Date: 2022-12-31
• Subjects: Electric vehicle (EV) -- direct torque control (DTC) -- team work optimisation (TOA) -- loss model-based control (LMC); Power resources -- Periodicals; Renewable energy sources -- Periodicals; 621.04205
• DOI: 10.1080/01430750.2022.2091036
• Languages: English
• ISSNs: 0143-0750

Abstract

Abstract : Electric vehicles (EVs) are a feasible alternative to traditional automobiles because of their silent operation and low emissions. Energy optimisation in EVs powered by induction motor (IM) drive is essential for lowering battery current. A loss model-based controller (LMC) is a popular approach that quickly converges to an optimum solution. Some LMC approximations, such as ignoring leakage inductances and iron loss, adversely influence IM drive performance in loss reduction. This work proposes an improved LMC in conjunction with direct torque control (DTC) to address the issue. Here, a parameter-free optimisation algorithm known as the teamwork optimisation algorithm (TOA) is used to select the optimum stator flux for improving IM efficiency. The algorithm is validated using realistic EV data and tested with standard drive cycles. The results demonstrate the improvement in efficiency and the reduction in torque ripple.