Electric and Hybrid Vehicle Technologies Open access Peer reviewed

Phase-Informed ECMS with Soft SOC Safeguarding for a Virtual Hybrid Agricultural Tractor

Chenyu Cui, Peng Wang, Yucheng Zhang

Energies | Oct 22, 2026

Abstract

Abstract

Fuel reductions can be confounded by battery depletion or unreported control corrections. This theoretical study examines phase-informed equivalent-consumption minimization (ECMS) with a soft state-of-charge (SOC) safeguard in an ideal power-split virtual tractor. The model includes planetary kinematics, machine limits, battery resistance and engine execution constraints. Numerical conservation checks verify implementation without providing empirical validation. The frozen adaptive configuration reproduces the submitted 5.676% normalized fuel saving. On 20 independent paths, it achieves 5.951% saving relative to matched load following, with all paths meeting a 10−4 terminal-SOC tolerance. Removing the safeguard leaves no terminal-valid paths. Removing adaptation instead gives 7.091% saving with the same safeguard, while increasing mean interventions from 94.8 to 150.5. Adaptation therefore changes the fuel–intervention trade-off rather than improving fuel economy. Same-parameter cycle, capacity and map audits retain positive valid-pair savings but expose terminal failures and an empty-action demand boundary. A historical approximately 20% full-information diagnostic is reported separately under a favorable map, different electrical limits and relaxed terminal band. The contribution is an auditable comparison of fuel, terminal charge and corrections within a declared virtual platform, without recursive-feasibility guarantees or field-economy predictions.

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Authors

Researchers on this paper

Chenyu Cui

first | Institute of Computing Technology | ORCID 0009-0005-1928-6218

Peng Wang

middle | Institute of Computing Technology

Yucheng Zhang

last | Institute of Computing Technology

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Citation

BibTeX

@article{Cui2026Phase,
  title = {Phase-Informed ECMS with Soft SOC Safeguarding for a Virtual Hybrid Agricultural Tractor},
  author = {Chenyu Cui and Peng Wang and Yucheng Zhang},
  journal = {Energies},
  year = {2026},
  doi = {10.3390/en19215024},
  url = {https://doi.org/10.3390/en19215024}
}

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