Battery Energy Management Techniques for an Electric Vehicle Traction System
نویسندگان
چکیده
This paper presents two battery energy management (BEM) techniques for an electric vehicle (EV) traction system which incorporates indirect field-oriented (IFO) induction motor (IM) drive system. The main objective of the proposed BEM is to regulate IM’s speed while minimizing lithium-ion (Li-ion) bank state charge (SOC) reduction and health (SOH) degradation. In contrast most existing work, operate without any prior knowledge driving profiles or road information. first technique cascaded fuzzy logic controllers (CSFLC). CSFLC, controller (FLC) generates reference current signal regulating speed, second FLC a variable gain that limits variation based on SOC. model predictive control (MPC) regulation. However, this work introduces new way tuning MPC input weight using It features tuned (FMPC), where adjusts in function such SOC considered generating command signal. Furthermore, utilizes model-in-loop strategy comprising Chen Mora (CM) experimentally obtained power consumption estimate increase runtime lifetime. A real-time implementation carried out prototype EV New European Drive Cycle (NEDC) Supplemental Federal Test Procedure (US06) cycles. experimental results validate CSFLC FMPC exhibit lower SOH degradation, thus prolonging lifetime as compared conventional regulators. Further experimentation demonstrates superiority over due lesser computational burden higher average saving.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3195940