A load-gradient coupling range-extended electric vehicle truck adaptive energy management method and system
By adopting an adaptive energy management method that couples load and slope, combined with low-latency operating condition perception and dual closed-loop optimization, the problem of energy distribution mismatch in range-extended electric logistics vehicles under complex operating conditions is solved, thereby improving fuel economy, power battery life, adaptability, and stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 无锡先进内燃动力技术创新中心
- Filing Date
- 2026-06-04
- Publication Date
- 2026-07-24
AI Technical Summary
Existing energy management solutions for range-extended electric logistics vehicles lack dual coupling considerations for load and gradient, resulting in mismatched energy distribution under complex working conditions, increased vehicle fuel consumption, drastic fluctuations in the state of charge (SOC) of the power battery, and a lack of real-time response capability, making it difficult to meet the actual needs of heavy-duty logistics vehicles.
By constructing an adaptive energy management method that couples load and slope, combined with low-latency operating condition perception, and adopting a two-dimensional classification of load level and slope type, a MIL model is built for offline optimization. Through iterative optimization and online correction using a genetic algorithm, dynamic SOC threshold adjustment and vehicle power distribution are achieved, thus constructing an offline-online dual closed-loop optimization architecture.
It improves the overall vehicle fuel economy, reduces power battery SOC fluctuations, extends battery life, enhances driving smoothness and energy management accuracy under complex operating conditions, and is compatible with existing heavy-duty logistics vehicle platforms without requiring additional hardware.
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