Research On Eco-Driving Of Intelligent Connected Hybrid Electric Vehicle Under Multi-Signal Intersections

The ’New Energy Vehicle Industry Development Plan(2021-2035)’,which clearly points out that by giving priority to the development of new energy vehicle technology.In order to solve the environmental pollution and energy crisis caused by vehicles.Among many energy-saving technologies,electric drive technology and eco-driving technology have excellent energy-saving potential.On the premise of meeting the demand power,eco-driving technology realizes energy saving and emission reduction by optimizing the vehicle speed according to road conditions,signal phase timing message(SPAT)and other conditions.With the development of automobile intelligence,networking and electrification,the energy-saving potential of eco-riving technology can be fully utilized.The eco-driving of hybrid electric vehicle is a coupling problem of speed planning and energy management.The co-optimization of hybrid electric vehicles is complex and computationally intensive.Therefore,for the eco-driving strategy of intelligent connected hybrid vehicles,how to make it have good optimality and excellent real-time potential is an urgent problem to be solved.This paper takes parallel hybrid electric vehicles as the research object.Based on the Pontryagin’s minimum principle(PMP),eco-driving optimal control problem under multi-signal intersections of parallel hybrid electric vehicle is solved by deriving the analytical solution of control variables.Speed planning and energy management are co-optimized.Make the ecodriving strategy have well optimality and excellent real-time potential.The research contents are as below:Firstly,the components of the parallel hybrid electric vehicle system are modeled.Assuming that the vehicle is driving on a flat road,the longitudinal dynamics model of the vehicle is established through the force analysis of the vehicle.The engine fuel consumption rate model and the motor power model are constructed by using the MATLAB fitting toolbox.Then,the dynamic programming(DP)algorithm is used to construct the single parameter shifting schedule model of the transmission under the typical urban bus condition(CTCC)in China.Finally,the battery state of charge(SOC)model is established according to the battery equivalent circuit model.Through the model construction of each part,it lays a model foundation for hybrid electric vehicle eco-driving research.Then,the eco-driving with multi-signal intersection in single vehicle scenario is studied,and the eco-driving strategy based on the analytical solution of control variables derived from PMP is proposed to co-optimize the speed and energy management.Firstly,in the scenario of single vehicle with multi-signal intersection,the inequality constraints of signal lights are transformed into equality constraints by calculating the time when the vehicle arrives at the signal intersection,so as to facilitate the calculation of subsequent co-optimization.Then,taking the signal intersection as a node,a piecewise eco-driving optimal control problem is established.Based on the necessary conditions of PMP,the analytical solution of control variables is derived,and an iterative loop algorithm is designed to determine the initial value of the co-state variables.Else the PMP and DP methods are compared and simulated.The simulation results show that the fuel consumption of the PMP co-optimization method is close to the DP method,but the calculation time is only 0.054%and 0.032%of the DP method,which proves the effectiveness of the method.Finally,the influence of the initial value of the co-state variable on the performance of PMP cooptimization is analyzed.Finally,the eco-driving with multi-signal intersection in the car-following scenario is studied.Combining the car-following control rules with the PMP co-optimization method,a car-following eco-driving strategy integrated with SPAT is proposed.Firstly,car-following scenario with multisignal intersection is established.Secondly,the safe car-following distance model is established,and the car-following distance constraint of the preceding vehicle is transformed into the limit of the maximum speed of the host vehicle,and a car-following control rule algorithm is proposed to ensure the safety of the vehicle Then the co-optimization method based on PMP is used to solve the problem to ensure the economy.Finally,in order to verify the effectiveness of the carfollowing eco-driving strategy integrated with SPAT,a comparative simulation analysis of the car-following eco-driving strategy with non-integrated SPAT is carried out.The simulation results show that compared with the non-integrated SPAT eco-driving strategy,the fuel consumption of the integrated with SPAT eco-driving strategy is reduced by 6.27%and 5.69%respectively in two different simulation scenarios,and the driving time is shorter,which proves the effectiveness of the strategy.