| With the development and progress of society,human demand for fossil energy continues to increase,energy and environmental problems have intensified,and the efficient and clean combustion of engines and the energy-saving and emission reduction of vehicles have become important research directions.Hybrid vehicles have the advantages of both traditional fuel vehicles and pure electric vehicles.They can significantly improve the power,economy,and emission performance of the vehicle,and avoid problems such as mileage anxiety.Therefore,they have received widespread attention.The RCCI combustion mode based on gasoline/diesel dual injection has good performance in terms of thermal efficiency and emissions.Due to its convenient combustion phase control and small changes to the original engine mechanical structure,it has become one of the most promising combustion modes currently.Hybrid electric vehicles include complex energy conversion,and need to manage the power source output according to the changing road conditions and vehicle conditions to ensure the best efficiency of the vehicle.Its energy management strategy determines the economy,power,and performance of the vehicle to a certain extent.Performance such as reliability has always been the focus of research in the field of hybrid power.The operating range of hybrid vehicle engines is narrower than that of traditional vehicle engines.However,the RCCI combustion mode has the problem of difficulty in load expansion due to restrictions such as engine pressure rise rate.The engine using RCCI combustion mode is used as a hybrid dedicated engine and is comparable to the hybrid system.The combination can achieve complementary advantages and realize energy saving and emission reduction of the whole vehicle.This subject is based on the Jilin Province Industrial Innovation Special Fund Project— "Development of Key Technologies for Energy Management of Hybrid Vehicles’ Special Engines and Power Systems"(Project No.: 2019C058-3),based on Converge and GT-power software to build gasoline/diesel dual-injection RCCI The combustion mode engine simulation model determines the optimization area according to the operating characteristics of the hybrid engine,and optimizes the combustion boundary conditions of the dual-fuel engine through co-simulation to obtain the universal characteristics of the dual-fuel engine.Compared with the universal characteristics of the original engine,the dual-fuel engine has a maximum thermal efficiency of44%,an increase of 3% compared to the original engine,and a minimum fuel consumption rate of189.28g/(k W·h),which is 8.39% lower than that of the original engine;more than 40% Take the thermal efficiency range as an example.The working range of the original machine is concentrated in the range of 1500-1800 r/min and 230-360 Nm,while the range of the dual-fuel engine with a thermal efficiency above 40% is widely distributed in the range of 1100-3200 r/min and 150-360 Nm.Internally,the thermal efficiency of the dual-fuel engine has been comprehensively improved,broadening the speed and load range of the high-efficiency zone.Since the engine operating conditions of parallel hybrid electric vehicles are not fixed and work in the form of surface operating conditions,the optimized dual-fuel engine is more suitable for hybrid power systems.The dual-fuel engine is more efficient at medium and high loads.When mounted on a parallel hybrid electric vehicle,it can avoid the engine from working in the low-efficiency area,and better exert its advantages of high efficiency and low fuel consumption.In this paper,a light commercial truck is transformed into a hybrid truck,and the power battery and motor are designed and selected.Based on AVL-Cruise,a hybrid vehicle simulation platform and a pure fuel vehicle simulation platform are constructed,using MATLAB/Simulink A logic threshold energy management strategy is constructed,and the energy management strategy is explored under the CHTC-LT test cycle and the dual-fuel engine is applied to the hybrid platform to improve the fuel consumption of the vehicle.The simulation results show that whether it is the original engine or the dual-fuel engine,the fuel saving rate of the hybrid platform is more than 10%compared with the pure fuel platform under the same condition of the engine;on the pure fuel platform,the dual fuel engine is more fuel-efficient than the original engine 21.2%.On the hybrid platform,the dual-fuel engine saves 6.54% fuel than the original engine,indicating that the dualfuel engine has greater fuel-saving potential than the original engine.Mounting it on the hybrid vehicle platform can create a more fuel-efficient combination.In order to further improve the economy of the whole vehicle,this paper constructs an energy management strategy based on fuzzy control.Under the condition that the engine remains unchanged and the initial SOC is different,the fuzzy strategy has a certain fuel-saving effect compared with the logic threshold strategy;in the fuzzy strategy No change,the dual-fuel engine has better fuel-saving effect than the original engine.Because the design of fuzzy strategy is subjective and cannot reach the optimum,this paper uses genetic algorithm to optimize the division point of the membership function of fuzzy strategy in the universe.The simulation results show that under the original engine conditions,the optimized fuel consumption is reduced by 7.89%,and under the dual-fuel engine conditions,the optimized fuel consumption is reduced by 9.05%,and the dual-fuel engine saves 7.2% compared to the original engine.The analysis shows that after the fuzzy strategy is optimized by the genetic algorithm,the engine intervention work time is reduced,and the high-efficiency work point accounts for a higher proportion.Compared with the original engine,the increase in the proportion of operating points in the high-efficiency zone of the dual-fuel engine is mainly concentrated in the high thermal efficiency area.This is one of the main factors for the dual-fuel engine to perform better than the original engine under the same optimized conditions. |