| Traditional fuel-powered buses emit a significant amount of tailpipe pollutants and greenhouse gases,causing serious environmental impacts.In contrast,pure electric buses have zero emissions,which can significantly reduce air pollution and greenhouse gas emissions,contributing to improved urban air quality and climate change mitigation.By studying the control strategies of fixed-route,two-speed automatic transmission pure electric buses,their efficiency and driving comfort can be further improved,promoting the widespread adoption of electric buses and facilitating the transition of urban transportation to clean energy.This article aims to investigate the operational performance and energy efficiency of a 12-meter pure electric bus on a fixed bus route.The research work includes collecting road gradient data of the bus route,designing the overall vehicle drivetrain matching,formulating shifting control strategies,and optimizing front and rear braking force distribution strategies.These research efforts contribute to improving the performance and energy efficiency of pure electric buses on fixed routes.Among them,the collection of road gradient data provides important data support for shifting control strategies and front and rear braking force distribution strategies,while the optimization of braking force distribution enhances the overall braking performance and safety of the vehicle.Through these research works,this paper aims to provide strong support for the application and promotion of pure electric buses on fixed bus routes.This article introduces the basic road conditions,passenger load,and urban bus driving conditions of Fuzhou City’s Minyun 901 bus route,and provides a detailed description of the method used to collect road gradient information of the bus route.The paper utilizes an extended Kalman filter fusion algorithm based on acceleration sensors,vehicle attitude sensors,and GPS sensors,and analyzes the error sources of different sensors.Subsequently,based on the national standards and actual driving conditions of pure electric buses,the drivetrain parameters of the electric motor,power battery,and gearbox are matched to ensure the vehicle’s performance.On this basis,a three-parameter fuel economy shifting control strategy is established,considering vehicle speed,acceleration,and road gradient,and is trained using a GA-BP neural network.In terms of braking force distribution,a braking control system is built,including fuzzy control-based braking intensity recognition,front and rear braking force distribution,and regenerative braking energy recovery strategy.In the strategy for front and rear braking force distribution,the optimal front axle distribution coefficient is obtained using optimization functions in MATLAB,taking into account the adhesion coefficient and braking intensity.Furthermore,the paper adopts a strategy based on the maximum regenerative braking force of the motor in the control strategy for regenerative braking energy recovery.Finally,combining the aforementioned control strategies,an integrated vehicle model is established using AVL-Cruise and MATLAB/Simulink,and dynamic and economic simulations are conducted to analyze the performance of the vehicle model.The research results indicate that the drivetrain parameter matching of pure electric buses can meet their power demands.By implementing front and rear braking force distribution control strategies,the overall braking performance and safety of the vehicle can be improved.In terms of fuel economy,the three-parameter-based shifting strategy is more energy-efficient compared to the shifting strategy based on driver experience.Additionally,the secondary distribution strategy of braking force based on the maximum regenerative braking force of the motor maximizes the recovery of energy generated by regenerative braking while ensuring vehicle safety,thereby enhancing the vehicle’s fuel economy and driving range. |
