Modelling & control of electric regenerative braking on a battery - IPMSM powered EV with fuzzy logic

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Τερζής, Κωνσταντίνος

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The deployment of Electric Regenerative Braking Systems (ERBS) in the contemporary Electric Vehicle (EV) and Electric - Hybrid Vehicle (EHV) industries as a method of reducing the carbon footprint of these vehicles and extending their range is prevalent. ERBS are a type of energy-recovery systems that work by operating the electric motor that is normally used for propulsion as a generator during braking, thereby providing a way of harvesting a part of the vehicle’s kinetic energy and converting it to electric energy which can be used to charge the battery. In most applications, conventional braking systems (CBS), for example, friction brakes, are used in conjunction with ERBS because of the power-absorbing limitations of the electric motor and the battery. A properly designed ERBS can help achieve multiple objectives crucial for the energy efficiency and overall performance of EVs/HEVs. More specifically, electric regenerative braking can extend the driving range by capturing and storing some of the kinetic energy that is normally converted into heat when conventional friction brakes are used, as well as prolong the lifetime of the battery and the mechanical braking system that is required to assist the regenerative braking system. The primary goal of this study is to develop a fuzzy rule-based method for the control of a Series Electric Regenerative Braking System (Series – ERBS) for a Front-Wheel-Drive (FWD) Electric Vehicle (EV) driven by an Internal Permanent Magnet Synchronous Motor (IPMSM). A comprehensive electric vehicle (EV) model is developed for this purpose, incorporating IPMSM powertrain, Electro–Hydraulic Braking (EHB), and Longitudinal Vehicle Dynamics (VD) modules. This is accomplished using the MathWorks Simulink system modeling software. The distribution of braking load on the vehicle’s front/rear axles is taken into consideration by examining three (3) distinct braking allocation methods: the Ideal Curve (I – Curve) method, the Fixed Ratio method, and a Composite (I – Curve, ECE Curve) method. The key objective of distributing the front axle braking load between the ERBS and the conventional braking system (which uses Disk Brakes) in a way that provides both adequate braking performance and optimal energy recovery is realized through the design of a Fuzzy Logic Controller that uses the motor speed, the required braking strength and the battery state of charge (SOC) as fuzzy inputs and yields a braking allocation factor as its output, which is then used to calculate the portion of the braking force which will be assigned on the CBS and the ERBS. The energy-recovery performance is evaluated by testing the proposed EV model and associated control system on a variety of standardized driving cycles that correspond to different braking requirements (urban or high-speed braking scenarios).



Electric vehicle (EV), Regenerative braking, Fuzzy logic, Internal permanent magnet synchronous motor (IPMSM), Electronic – hydraulic braking (EHB)