Research On Optimization Of PHEV Energy Management Strategy Considering Traffic Signal Information

In recent years,with the continuous enhancement of China’s economic strength and the rapid improvement of people’s quality of life,automobiles have entered every household as the main tool of passage.However,with the continued growth of car ownership,the country is also facing severe tests of environmental pollution and energy consumption.Only by getting rid of the traditional internal combustion engine and fully using the electric motor can the current crisis be effectively alleviated,however,due to factors such as the low range of pure electric vehicle,poor battery stability in poor environments and imperfect charging facilities,most users still prefer traditional internal combustion engine vehicle as their main travel tool in a short period of time.As the emission standards become stricter year by year,while hybrid vehicle combines the advantages of both,not only does it retain the long-range endurance characteristics of the internal combustion engine,but also continue the advantages of pure electric vehicle to save energy,effectively improving the fuel economy of the entire vehicle.Therefore,China is stepping up its efforts to research and develop hybrid electric vehicle(HEV).This paper focuses on how plug-in hybrid electric vehicle(PHEV)can minimize the equivalent fuel consumption through intersections in a connected vehicle environment.The main contents include the following aspects:(1)In a connected-vehicle network environment,the information of road intersections is known in advance,the traffic patterns of single vehicle and multi-vehicles without stopping through continuous intersections are analyzed,the speed range of each mode is solved,and the decision-making model of passing through continuous intersections without stopping is established.(2)Based on the existing HEV assembly structure,an electric motor is added to analyze the vehicle’s power system.The working mode of the HEV is mainly composed of the engine working mode,pure electric mode,stroke charging mode,hybrid drive mode,and braking energy recovery mode.Based on Matlab/Simulink,motor model,longitudinal dynamic model,driver model,engine model and battery model are established.(3)The genetic algorithm is used to solve the non-stop speed range,the minimum fuel consumption is used as the objective function,the road speed limit,signal information and other constraints are established,and the equivalent factor is optimized offline according to the differentiated driving conditions to establish the multi-objective correction factor GA-ECMS Strategy.(4)This paper proposes that the PHEV does not stop through the continuous intersection strategy in the internet of vehicles environment.Compared with the PHEV simulation result of the continuous intersection strategy without predicting the intersection information,the average time for the signal vehicle to pass the continuous signal is shortened by 4.3%,and the average equivalent fuel reduced consumption by 17.6%.The average time taken by the multi-vehicle follow-up method through continuous intersections were reduced by 2.9%,and the average equivalent fuel consumption was reduced by 13.9%.It is verified that the strategy optimization proposed in this paper effectively improves the fuel economy of the entire vehicle,and further alleviates the environmental pollution and energy consumption problems that my country is facing,which is also of great significance to the development of the automotive industry.