Eco-driving Control Strategy For Intelligent Fuel Cell Vehicles In Complex Driving Conditions

In recent decades,fuel-cell hybrid electric vehicles(FCHEV)development has achieved great success.With its advantages of zero pollution,high energy density and high efficiency,it has made full use of hydrogen energy and is considered the most promising ideal vehicle.Nevertheless,the uncertain factors in the dynamic traffic environment have caused significant difficulties for the speed planning and energy management of FCHEV.Thus,based on the National Natural Science Foundation project "Robust Control Research on Intelligent Heavy-duty Semi-trailer Dynamic Lanechanging Multi-mode Switching for Complex Traffic Environment"(52262053),the basic research project of Yunnan Science and Technology Plan in 2021 "Study on Stability Control Strategy of Heavy-duty Semi-trailer under Complex Working Conditions of Mountainous Expressway Considering Dynamic Changes of Pavement Parameters"(202101AT070108)and “Talent support project in Xingdian”,this paper focuses on studying the eco-driving of FCHEV to enhance vehicle energy economics in various dynamic traffic environments.Firstly,this study analyses the advantage/disadvantages of several basic configurations of FCHEVs.By considering the operating scenarios,the powertrain configuration of “fuel cell + power battery” is employed as the research object.Subsequently,the parameter match and model simplified for fuel cell and battery are conducted.Additionally,the source of resistance during the driving is studied and the vehicle dynamic model is established.Meanwhile,the input-output characteristic relationship of the motor in different operating modes is discussed.Subsequently,the overall framework and workflow of speed planning and energy management are analysed.Considering the influence of the future driving state of the vehicle on the safety and economy,and the low prediction efficiency and accuracy of the existing speed planning strategy,this paper utilizes the gradient-based MPC(GRAMPC)based on the projected gradient method to execute the upper layer speed optimization,which can significantly improve the operation efficiency and calculation accuracy.Further,the multi-objective evaluation indicators such as hydrogen consumption,battery degradation,SOC and global cost are employed to comprehensively evaluate the performance of the designed energy management.To explore the eco-driving strategy in a dynamic and complex environment,the typical urban traffic setting is selected as the research goal,which aims to enhance the economy when passing through the traffic signal.Consequently,a braking energy recovery strategy based on fuzzy rules is emphatically designed by considering vehicles’ frequent acceleration and deceleration characteristics in signal intersections.The results display that compared with fixed braking distribution coefficient,it can remarkably improve the energy-saving effect.Subsequently,the dynamic distribution of the preceding and rear vehicle is incorporated in the simulation,the simulation results suggested that the FCHEV can avoid the collision with the preceding and rear vehicle and pass through the intersection.Additionally,the energy economy is significantly improved compared with the cruise driving state.Besides,the critical safe speed under different curved curvatures is determined in the continuous curved scenario.Considering the influence of vehicle driving state on energy management,the power ratio-based Adaptive Equivalent Consumption Minimization Strategy(PR-AECMS)is designed to satisfy the equivalent factor of realtime change with vehicle state and improve energy efficiency.Ultimately,the simulation in a complex and dynamic traffic environment with preceding and rear vehicle distribution is executed.The terminal results illustrate that the developed strategy can dramatically improve the energy economy of FCHEV and ensure stability and safety in the curving section.