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Multi-input model predictive speed control of lean-burn natural gas engine in range-extended electric vehicles

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  • Xiong, Wenyu
  • Ye, Jie
  • Gong, Qichangyi
  • Feng, Han
  • Xu, Jinbang
  • Shen, Anwen

Abstract

This study presents a multi-input model predictive speed control of lean-burn natural gas engine in a range extender to improve the responsiveness and anti-disturbance ability of the system. Lean combustion is recognized as an effective strategy to improve the economy and emission performance of the natural gas engine. However, the engine torque is insufficient compared with a normal combustion mode, which will result in a degraded anti-disturbance and low response performance in an engine speed tracking system in the range extender. In order to improve the performance of the lean-burn gas engine speed system, the air-fuel ratio (AFR) additional torque is introduced as another input of the system besides the throttle valve to increase the engine transient output torque, where the AFR additional torque is produced by setting AFR deviation from the nominal value. A multi-input model predictive control (MPC) controller is designed to handle the multiple inputs and constraints, guaranteeing that the AFR returns to the nominal value at steady state for efficiency and emissions, and an improved fast MPC algorithm is proposed to reduce the computation effort of the MPC strategy. Moreover, the proposed controller is evaluated by co-simulations on the platform of Matlab/Simulink with GT-Power and experiments on a range extender.

Suggested Citation

  • Xiong, Wenyu & Ye, Jie & Gong, Qichangyi & Feng, Han & Xu, Jinbang & Shen, Anwen, 2022. "Multi-input model predictive speed control of lean-burn natural gas engine in range-extended electric vehicles," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221024130
    DOI: 10.1016/j.energy.2021.122165
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    References listed on IDEAS

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    1. Shen, Xun & Zhang, Yahui & Shen, Tielong & Khajorntraidet, Chanyut, 2017. "Spark advance self-optimization with knock probability threshold for lean-burn operation mode of SI engine," Energy, Elsevier, vol. 122(C), pages 1-10.
    2. Ran, Zhongnan & Hariharan, Deivanayagam & Lawler, Benjamin & Mamalis, Sotirios, 2020. "Exploring the potential of ethanol, CNG, and syngas as fuels for lean spark-ignition combustion - An experimental study," Energy, Elsevier, vol. 191(C).
    3. Xu, Zidan & Zhang, Yahui & Di, Huanyu & Shen, Tielong, 2019. "Combustion variation control strategy with thermal efficiency optimization for lean combustion in spark-ignition engines," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
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    2. Cruz, José Ramón Serrano & López, J. Javier & Climent, Héctor & Gómez-Vilanova, Alejandro, 2023. "Method for turbocharging and supercharging 2-stroke engines, applied to an opposed-piston new concept for hybrid powertrains," Applied Energy, Elsevier, vol. 351(C).

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