An Energy Saving MTPA-Based Model Predictive Control Strategy for PMSM in Electric Vehicles Under Variable Load Conditions
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| Veröffentlicht in: | Computation vol. 13, no. 10 (2025), p. 231-250 |
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| 022 | |a 2079-3197 | ||
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| 045 | 2 | |b d20251001 |b d20251031 | |
| 084 | |a 231446 |2 nlm | ||
| 100 | 1 | |a Gao Lihua |u College of Electrical Engineering and Control Science, Nanjing Polytechnic Institute, Nanjing 210048, China; gaolihua@njpi.edu.cn (L.G.); mak@njpi.edu.cn (K.M.) | |
| 245 | 1 | |a An Energy Saving MTPA-Based Model Predictive Control Strategy for PMSM in Electric Vehicles Under Variable Load Conditions | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a To promote energy efficiency and support sustainable electric transportation, this study addresses the challenge of real-time and energy-optimal control of permanent magnet synchronous motors (PMSMs) in electric vehicles operating under variable load conditions, proposing a novel Laguerre-based model predictive control (MPC) strategy integrated with maximum torque per ampere (MTPA) operation. Traditional MPC methods often suffer from limited prediction horizons and high computational burden when handling strong coupling and time-varying loads, compromising real-time performance. To overcome these limitations, a Laguerre function approximation is employed to model the dynamic evolution of control increments using a set of orthogonal basis functions, effectively reducing the control dimensionality while accelerating convergence. Furthermore, to enhance energy efficiency, the MTPA strategy is embedded by reformulating the current allocation process using d- and q-axis current variables and deriving equivalent reference currents to simplify the optimization structure. A cost function is designed to simultaneously ensure current accuracy and achieve maximum torque per unit current. Simulation results under typical electric vehicle conditions demonstrate that the proposed Laguerre-MTPA MPC controller significantly improves steady-state performance, reduces energy consumption, and ensures faster response to load disturbances compared to traditional MTPA-based control schemes. This work provides a practical and scalable control framework for energy-saving applications in sustainable electric transportation systems. | |
| 653 | |a Load | ||
| 653 | |a Electric vehicles | ||
| 653 | |a Accuracy | ||
| 653 | |a Torque | ||
| 653 | |a Control algorithms | ||
| 653 | |a Cost function | ||
| 653 | |a Orthogonal functions | ||
| 653 | |a Optimization | ||
| 653 | |a Transportation systems | ||
| 653 | |a Predictive control | ||
| 653 | |a Basis functions | ||
| 653 | |a Synchronous motors | ||
| 653 | |a Variables | ||
| 653 | |a Energy efficiency | ||
| 653 | |a Laguerre functions | ||
| 653 | |a Renewable energy | ||
| 653 | |a Optimal control | ||
| 653 | |a Real time | ||
| 653 | |a Energy consumption | ||
| 653 | |a Permanent magnets | ||
| 653 | |a Energy conservation | ||
| 700 | 1 | |a Lv Xiaodong |u College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China; szh@njtech.edu.cn | |
| 700 | 1 | |a Ma, Kai |u College of Electrical Engineering and Control Science, Nanjing Polytechnic Institute, Nanjing 210048, China; gaolihua@njpi.edu.cn (L.G.); mak@njpi.edu.cn (K.M.) | |
| 700 | 1 | |a Shi Zhihan |u College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China; szh@njtech.edu.cn | |
| 773 | 0 | |t Computation |g vol. 13, no. 10 (2025), p. 231-250 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3265849547/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3265849547/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3265849547/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |