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Basic Introduction of New Energy Vehicles Structure and Research Progress on Fault Detection Methods of New Energy Vehicles
by
Ling, Hao
in
Chassis
/ Electric vehicles
/ Fault detection
/ Internal combustion engines
/ Maintenance
/ Vehicle safety
2025
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Basic Introduction of New Energy Vehicles Structure and Research Progress on Fault Detection Methods of New Energy Vehicles
by
Ling, Hao
in
Chassis
/ Electric vehicles
/ Fault detection
/ Internal combustion engines
/ Maintenance
/ Vehicle safety
2025
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Basic Introduction of New Energy Vehicles Structure and Research Progress on Fault Detection Methods of New Energy Vehicles
Journal Article
Basic Introduction of New Energy Vehicles Structure and Research Progress on Fault Detection Methods of New Energy Vehicles
2025
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Overview
In the booming automotive industry, automotive fault detection is crucial. This study focuses on electric vehicle chassis. It first details the basic structure of the electric vehicle chassis, including its four-part system (transmission, driving, steering, and braking), and the differences in chassis structures between traditional and new energy vehicles. Also, it elaborates on common chassis materials, with distinct choices for conventional internal combustion engine vehicles (prioritizing safety and performance) and electric vehicles (emphasizing lightweight for energy efficiency). Regarding maintenance methods, the OBD system, a prevalent diagnostic tool in new energy vehicles, offers detailed performance data and fault codes, ensuring vehicle safety and enabling remote diagnosis and software updates. The Application of Electronic Diagnosis Technology is more suitable for new energy vehicles due to their complex electronics, though it has limitations. The study concludes that current fault detection methods are becoming more complete. By introducing chassis structure, materials, and two detection methods OBD system and Electronic Diagnosis Technology, it aims to improve automotive fault detection. Future research should refine the display of fault detection results to enhance maintenance efficiency.
Publisher
EDP Sciences
Subject
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