Abstract

The highly efficient Interior Permanent Magnet Synchronous Motor (IPMSM) is ubiquitous choice in Electric Vehicles (EVs) for today’s automotive industry. IPMSM control requires accurate knowledge of an immeasurable critical Permanent Magnet (PM) flux linkage parameter. The PM flux linkage is highly influenced by operating temperature which results in torque derating and hence power loss, unable to meet road loads and reduced life span of electrified powertrain in EVs. In this paper, novel virtual sensing scheme for estimating PM flux linkage through measured stator currents is designed for an IPMSM centric electrified powertrain. The proposed design is based on a Uniform Robust Exact Differentiator (URED) centric Super Twisting Algorithm (STA), which ensures robustness and finite-time convergence of the time derivative of the quadrature axis stator current of IPMSM. Moreover, URED is able to eliminate chattering without sacrificing robustness and precision. The proposed design detects variation in PM flux linkage due to change in operating temperature and hence is also able to establish characteristics of fault detection. The effectiveness and accuracy in different operating environments of the proposed scheme for nonlinear mathematical IPMSM model with complex EV dynamics are verified thorough extensive simulation experiments using MATLAB/Simulink.

Highlights

  • The rising awareness of climate change activities including global warming, transition to clean energy with vision of zero-emission vehicles and rapid decline of fossil fuels collates for electrifying the automotive industry—due to which many automotive industry players (OEMs, investors, suppliers, startups, and so on) are making sizeable investment decisions for survival and profitability.In order to cope up with the challenges in Electric Vehicles (EVs) including but not limited to sustainability, high performance, high efficiency, and affordability in EV, ranging from Battery Electric Vehicle (BEV), Fuel Cell Electric Vehicle (FCEV), Plugin Hybrid Electric Vehicle (PHEV), and Hybrid Electric Vehicle (HEV), the car industry is going under radical transformation in electrified powertrain [1].1.1

  • In order to cope up with the challenges in EVs including but not limited to sustainability, high performance, high efficiency, and affordability in EV, ranging from Battery Electric Vehicle (BEV), Fuel Cell Electric Vehicle (FCEV), Plugin Hybrid Electric Vehicle (PHEV), and Hybrid Electric Vehicle (HEV), the car industry is going under radical transformation in electrified powertrain [1]

  • A virtual sensor using an Super Twisting Algorithm (STA) based Uniform Robust Exact Differentiator (URED) for Permanent Magnet (PM) flux linkage online estimation has been designed by considering nonlinear Interior Permanent Magnet Synchronous Motor (IPMSM) centric EV

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Summary

Introduction

The rising awareness of climate change activities including global warming, transition to clean energy with vision of zero-emission vehicles and rapid decline of fossil fuels collates for electrifying the automotive industry—due to which many automotive industry players (OEMs, investors, suppliers, startups, and so on) are making sizeable investment decisions for survival and profitability. In order to cope up with the challenges in EVs including but not limited to sustainability, high performance, high efficiency, and affordability in EV, ranging from Battery Electric Vehicle (BEV), Fuel Cell Electric Vehicle (FCEV), Plugin Hybrid Electric Vehicle (PHEV), and Hybrid Electric Vehicle (HEV), the car industry is going under radical transformation in electrified powertrain [1]

Electrified Powertrain
Related Work
Major Contributions
Virtual Sensor Development Strategy
Simulation Experiments
Simulator Design
Estimating/Sensing of an Immeasurable Parameter
Findings
Conclusions

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