Research On Predictive Energy Saving Control Strategy Of Commercial Vehicle

With the rapid development of economy,the road freight volume and cargo turnover of our country have increased year by year,so as to the sales and ownership of commercial vehicles.The problem of energy consumption of road transportation gradually becomes not negligible.Therefore,the research on energy-saving control of commercial vehicles is of great significance.Relying on the intelligent and connected vehicle technology,through the vehicle wireless communication technology to obtain real-time driving environment information,carry out predictive analysis and decision-making,realize the independent adjustment of vehicle state,will effectively improve the adaptability and control effect of commercial vehicle energy-saving control strategy,and play an important role in reducing vehicle energy consumption.According to the driving characteristics of commercial vehicles in road transportation,supported by Science and Technology Project of Jilin Provincial Department of Education“Distributed electric vehicle dynamic and collaborative control based on chassis-by-wire system”(Project Number :JJKH20200963KJ),this paper compares and analyzes the existing research status at home and abroad,summarizes the research progress of predictive energysaving control and transmission shift schedule,and designs the research content.Firstly,the gearshift schedule of the transmission is optimized based on the fuel consumption characteristics of the engine of commercial vehicle to improve its fuel economy.Secondly,a predictive energy-saving control strategy suitable for commercial vehicles is developed by combining steady-state control with dynamic control based on intelligent and connected vehicle technology.Finally,the effectiveness of the proposed control algorithm is verified by building a hardware in the loop test bench of commercial vehicles.The main contents of this paper are summarized as follows:(1)In order to establish predictive energy-saving control strategy,the longitudinal dynamics model of vehicle transmission system and braking system is established firstly,and the driving state of vehicle model is switched based on acceleration threshold.In the model of vehicle transmission system,the gearshift schedule of the transmission is optimized by using the fuel consumption characteristics of the vehicle engine to improve its fuel economy;in the vehicle braking system model,the electronically controlled pneumatic braking system model is established to dynamically distribute the braking force according to the vertical load of each axle,so that the braking performance is ensured.(2)Aiming at the long-distance driving condition of vehicles,the road height information is obtained by combining with intelligent and connected vehicle technology,and the steady-state speed curve of vehicles is planned by using model predictive control,which is the support condition of local dynamic planning of subsequent vehicles under typical driving conditions.Among them,in order to overcome the nonlinear characteristics in the process of vehicle driving state transition,the vehicle longitudinal dynamic linear model is calculated by linearization of vehicle energy change relationship.At the same time,the ride coefficient is added in the control process to prevent the sudden change of vehicle speed curve and affect the vehicle comfort.(3)In view of the typical working conditions such as speed limit section,low adhesion road and traffic intersection encountered in the process of vehicle driving,the typical working condition information extracted by the vehicle through intelligent and connected vehicle technology is taken as the quantitative constraint condition of speed limit.Based on the results of steady-state planning,both safety and comfort of vehicle driving are taken into account,and the optimal solution of vehicle speed at each stage is solved based on the Bellman dynamic programming algorithm to obtain the optimal speed curve of the vehicle during typical driving conditions.The target of reducing vehicle fuel consumption is achieved during the dynamic driving of the vehicle.(4)Build commercial vehicle hardware in the loop test bench.The model of braking system is embedded into the software,and the predictive energy-saving control strategy is realized in MATLAB/Simulink,Lab VIEW RT and Truck Sim RT are used as software support to provide driving scenarios,NI-PXI and d SPACE are used as hardware controllers,and the disc brake and brake valve of the braking system are used as actuators,so that the hardware in the loop verification of predictive energy saving control strategy is completed.