Multi-Objective Optimization Control of Diesel Engine Combustion Process Based on Model-Free Adaptive Control

To achieve multi-parameter and multi-objective optimal control of the diesel engine combustion process, a model-free adaptive enhanced control method for diesel engines was proposed. By analyzing the influences of algorithm parameters on system performance in model-free adaptive control and optimizing them with the particle swarm optimization algorithm, the robustness and adaptability of the control algorithm were improved. Experimental validation results demonstrate that the optimal algorithm parameters vary under different operating conditions. The enhanced model-free adaptive control algorithm optimized by the particle swarm algorithm achieves coordinated optimization of nitrogen oxide emissions and fuel economy under various load conditions. Specifically, fuel consumption and nitrogen oxide emissions were reduced by 2.52% and 5.38%, respectively, while the tracking control error remained within ±3%. The execution time of the control algorithm was 2.23 ms, realizing real-time multi-objective optimal control of the diesel engine combustion process.