Economic Analysis And Optimal Control Of Energy Consumption Of Electric Vehicles In Hilly Areas

With the comprehensive promotion of new energy vehicles in China,more and more automobile manufacturers have joined in the battle for the market of new energy.Battery electric vehicle(BEV),as one of the most important category in new energy vehicles,has the advantages such as energy conservation and environmental protection,simple structure,convenience maintenance,etc.Under the premise of these advantages,it has become the development trend of the new era to fully improve the economy and intelligence degree of automobiles.Aiming at battery electric vehicle,this paper studies the economic analysis of electric vehicles in hilly areas and proposes an adaptive cruise control(ACC)method based on energy optimization,which not only conforms to the era theme of energy conservation and environmental protection,but also meets the development needs of intelligence in the new era.Firstly,conduct dynamic system modeling for the transmission system structure and the parameters of the battery electric vehicle,mainly including transmission system dynamics model,motor energy consumption model,battery model and vehicle inverse dynamics model,which are the basis of algorithm construction and experimental simulation.Secondly,based on the vehicle model built,dynamic programming algorithms(DP)are used in hilly areas to reasonably allocate the working points of the motors to solve the global optimal speed trajectory with the lowest energy consumption.At the same time,according to the simulated vehicle model and its parameters,the corresponding optimal economic vehicle speed is calculated.Calculate the energy consumption of driving at the global optimal speed,and the energy consumption of driving at the economic speed and the nearby speed,and compare the calculated energy consumption to verify the rationality of the dynamic programming algorithm to optimize the speed on the actual road gradient.After that,in order to analyze the impact of the slope on the vehicle economy in hilly areas,on the premise of meeting the requirements of road slope design,by building the virtual slope data with different representativeness,consider the impact of different road slope changes on the economy of electric vehicles at different speeds,and simulate on the actual road slope.The test results show that the optimization of vehicle speed for different slopes can effectively improve the driving economy.Finally,in order to make the vehicle follow the globally optimal vehicle speed trajectory,this paper takes the vehicle speed as the reference trajectory speed of adaptive cruise control,and studies the adaptive cruise control algorithm to realize adaptive cruise control considering energy optimization.The adaptive cruise control adopts the hierarchical control mode.The upper controller uses the model predictive control(MPC)algorithm to solve the quadratic programming problem based on the built longitudinal kinematic relationship of the two vehicles,and complete the solution of the output desired acceleration.According to the vehicle inverse dynamics model,the lower controller realizes the operation of torque distribution and completes the function of the adaptive cruise system.The experimental results show that the adaptive cruise control method based on energy optimization proposed in this paper can effectively reduce energy consumption on the basis of realizing adaptive cruise control,so as to improve the mountain vehicles' economy and intelligence degree,and plays an important role in the study of energy-saving and intelligence of battery electric vehicles.