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Dual-Mode PID Control for Automotive Resolver Angle Compensation Based on a Fuzzy Self-Tuning Divide-and-Conquer Framework

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Publicat a:World Electric Vehicle Journal vol. 16, no. 10 (2025), p. 546-564
Autor principal: Zeng Xin
Altres autors: Wang Yongyuan, Zhu, Julian, Chu Yubo, Li, Hao, Peng Hao
Publicat:
MDPI AG
Matèries:
Accuracy
Proportional integral derivative
Self tuning
Powertrain
Resolvers
Magnetic fields
Electric vehicles
Optimization
Adaptation
Fuzzy logic
Compensation
Embedded systems
Physics
Control algorithms
Fault diagnosis
Coordinate transformations
Sensors
Electromagnetic interference
Controllers
Deviation
Program verification (computers)
Compliance
Real time
Control methods
Systems stability
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Resum:Electric vehicle (EV) drivetrains often suffer from degraded control precision due to resolver zero-position deviation. This issue becomes particularly critical under diverse automotive-grade operating conditions, posing challenges for achieving reliable and efficient drivetrain performance. To tackle this problem, we propose a dual-mode PID dynamic compensation control methodology. This approach establishes a divide-and-conquer framework that differentiates between weak-magnetic and non-weak-magnetic regions. It integrates current loop feedback with a fuzzy self-tuning mechanism, enabling real-time dynamic compensation of the resolver’s initial angle. To ensure system stability under extreme automotive conditions (−40 °C to 125 °C, ±0.5 g vibration, and electromagnetic interference), a triple-redundancy architecture is implemented. This architecture combines hardware filtering, software verification, and fault diagnosis. Our contribution lies in presenting a reliable solution for intelligent EV drivetrain calibration. The proposed method effectively mitigates resolver zero-position deviation, not only enhancing drivetrain performance under challenging automotive environments but also ensuring compliance with ISO 26262 ASIL-C safety standards. This research has been validated through its implementation in a 3.5-ton commercial logistics vehicle by a leading automotive manufacturer, demonstrating its practical viability and potential for widespread adoption in the EV industry.
ISSN:2032-6653
DOI:10.3390/wevj16100546
Font:Engineering Database