Abstract

Permanent magnet machines (PMs) equipped with fractional slot concentrated windings (FSCWs) have been preferably proposed for electric vehicle (EV) applications. Moreover, integrated on-board battery chargers (OBCs), which employ the powertrain elements in the charging process, promote the zero-emission future envisaged for transportation through the transition to EVs. Based on the available literature, the employed machine, as well as the adopted winding configuration, highly affects the performance of the integrated OBC. However, the optimal design of the FSCW-based PM machine in the charging mode of operation has not been conceived thus far. In this paper, the design and multi-objective optimization of an asymmetrical 12-slot/10-pole integrated OBC based on the efficient magnetic equivalent circuit (MEC) approach are presented, shedding light on machine performance during charging mode. An ‘initial’ surface-mounted PM (SPM) machine is first designed based on the magnetic equivalent circuit (MEC) model. Afterwards, a multi-objective genetic algorithm is utilized to define the optimal machine parameters. Finally, the optimal machine is compared to the ‘initial’ design using finite element (FE) simulations in order to validate the proposed optimization approach and to highlight the performance superiority of the optimal machine over its initial counterpart.

Highlights

  • Battery chargers can either be installed at charging stations, known as off-board chargers, or mounted on electric vehicles (EVs), known as on-board chargers

  • Most of the previous multi-objective optimization strategies were mainly based on numerical techniques such as 2D and 3D finite element (FE) models, recent literature has proposed some alternatives based on parametric magnetic equivalent circuit (MEC) models [13], which is a notable contribution of this analysis

  • Design optimization of Permanent magnet machines (PMs) machines using both FE and MEC models has been thoroughly discussed in the literature under the propulsion mode of operation [18]; this paper proposes the design and optimization of an integrated on-board battery chargers (OBCs) using an asymmetrical six-phase 12-slot/10-pole surface-mounted PM (SPM) machine based on the efficient parametric MEC approach

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Summary

Introduction

Battery chargers can either be installed at charging stations, known as off-board chargers, or mounted on electric vehicles (EVs), known as on-board chargers. Most of the previous multi-objective optimization strategies were mainly based on numerical techniques such as 2D and 3D finite element (FE) models, recent literature has proposed some alternatives based on parametric magnetic equivalent circuit (MEC) models [13], which is a notable contribution of this analysis. Design optimization of PM machines using both FE and MEC models has been thoroughly discussed in the literature under the propulsion mode of operation [18]; this paper proposes the design and optimization of an integrated OBC using an asymmetrical six-phase 12-slot/10-pole SPM machine based on the efficient parametric MEC approach. In [8], the influence of various design parameters, namely the slot-opening width and PM width to pole pitch ratio, on the torque ripple and core losses under both modes of operation was thoroughly addressed, and the optimal solution was selected based on the Pareto optimization technique. Improved electromagnetic performances, namely, torque profile and core losses, under both operational modes were obtained and validated using finite element analysis (FEA)

Design Requirements and Integrated EV Charging Application
S4 B2 S5 C2
A2 B1 B2 C1
Optimization Model
Overview of the Overall Design Optimization Process
Comprehensive Sensitivity Analysis
Flowchart of the Design Optimization Approach
Multi-Objective Optimization Approach
Box–Behnken Response Surface Method
Finite Element Validation
Conclusions
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