Multi-objective optimization of two-stroke compression release braking performance of a heavy-duty engine based on non-dominated sorting genetic algorithm II (NSGA II)

Abstract

Traditional heavy-duty vehicle service brakes use the friction method to realize vehicle deceleration, which means that longer-term use of the service brake will lead to overheating. It will make the braking capacity significantly reduced, at the same time, the service brake system also will wear much faster. Engine brake has been developed continuously in recent decades since it has the advantages of small install space and weight, no attenuation of braking power, rapid response, and endurance braking. However, the complex structure and large valve load of the valve train are the main obstacles to the widespread use of two-stroke compression release braking. Two-stroke compression release braking power is the effective indicator of the braking capacity and the maximum cylinder pressure (Pmax) can reflect the load of the valve train, therefore, the braking power and Pmax need to be optimized at the same time. In this paper, the multi-objective non-dominated sorting genetic algorithm II (NSGA II) was introduced to optimize the two-stroke compression release braking performance and it was compared with the orthogonal design method. The results indicated that the braking power and Pmax of optimal solution 1 by NSGA II achieved −395.64 kW and 59.37 bar, which were 1.17% and 2.78% improved than that of orthogonal analysis, respectively. In addition, the calculation process shows that NSGA II provides a more comprehensive and reliable method to optimize the valve parameters of the two-stroke compression release brake.