Abstract
In this paper, the air-fuel ratio regulation problem of compressed natural gas (CNG) engines is considered by employing stochastic model predictive control (MPC) technology. A stochastic model predictive regulator based on a discrete-time dynamic model of CNG engines is proposed, taking into account the residual gas, and the closed-loop system is deduced to be stochastically stable. A numerical simulation is performed to demonstrate the effectiveness of the proposed control scheme under two working conditions. The simulation results show that the performance of the proposed stochastic model predictive regulator is better than that of the open-loop controller.
Highlights
INTRODUCTIONThe emission and combustion performance of a natural gas engine with excess hydrogen, which is affected by the compression ratio under diverse air-fuel ratios has been described in [3]
Natural gas is a widely acknowledged apposite alternative fuel that can help improve the environment and address energy issues, owing to its widespread distribution, clean-burning properties and higher proportion of hydrogen to carbon [1]
This paper proposes a stochastic model predictive control (MPC) regulator based on a dynamic model of compressed natural gas (CNG) engines in the discrete-time form, which contains the air path and fuel path dynamics
Summary
The emission and combustion performance of a natural gas engine with excess hydrogen, which is affected by the compression ratio under diverse air-fuel ratios has been described in [3]. Sun: Stochastic MPC-Based Air-Fuel Ratio Regulation of CNG Engines considerably influences the control accuracy of the air-fuel ratio. The regulation problem of the air-fuel ratio of CNG engines is addressed by using a stochastic MPC algorithm based on the air path and fuel path dynamics. The control accuracy of the air-fuel ratio is improved, since the statistical information of the residual gas transitions is fully utilized, and the influence of the inaccuracy of the dynamic model is eliminated by using a stochastic model predictive regulator. A numerical simulation is performed to demonstrate the effectiveness of the employed air-fuel ratio stochastic model predictive regulator
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