Variable‐Structure Control with Complementarity‐Inputs for a Lean‐Burn IC Engine of a Series Hybrid Vehicle

Roqueiro, Nestor; Fossas, Enric; Oliveira, Amir Antônio Martins; Puleston, Pablo Federico

doi:10.1002/asjc.1000

Cited by 1 publication

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“…Lean burn technology for spark ignition (SI) engine control in research and industry has drawn a lot of attention around the world due to its fuel economy and lower carbon dioxide emissions. To achieve these goals, the SI engine needs to be operated and controlled at a relatively high AFR value (i.e., higher than stoichiometric value).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Sliding‐mode Strategy for Air–fuel Ratio Control of Lean‐burn Spark Ignition Engines

Wu¹,

Tafreshi²

2017

Asian Journal of Control

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Minimization of emissions of carbon dioxide and harmful pollutants and maximization of fuel economy for lean-burn spark ignition (SI) engines relies to a large extent on precise air-fuel ratio (AFR) control. However, the main challenge of AFR control is the large time-varying delay in lean-burn engines. Since the system is usually subject to external disturbances and uncertainties, a high level of robustness in AFR control design must be considered. We propose a fuzzy sliding-mode control (FSMC) to track the desired AFR in the presence of periodic disturbances. The proposed method is model free and does not need any system characteristics. Based on the fuzzy system input-output data, two scaling factors are first employed to normalize the sliding surface and its derivative. According to the concept of the if-then rule, an appropriate rule table for the logic system is designed. Then, based on Lyapunov stability criteria, the output scaling factor is determined such that the closed-loop stability of the internal dynamics with uniformly ultimately bounded (UUB) performance is guaranteed. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated under various operating conditions. The baseline controllers, namely, a PI controller with Smith predictor and sliding-mode controller, are also used to compare with the proposed FSMC. It is shown that the proposed FSMC has superior regulation performance compared to the baseline controllers.

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Section: Introductionmentioning

confidence: 99%