| In the face of increasingly severe energy stress,environmental pollution and driving safety,distributed drive electric vehicles(EVs)with the advantages of compact structure,high controllable freedom,fast and accurate control response have become the focus of the automotive industry and the future of automotive technology,also is the main development direction of future automotive technology.This trend puts higher demands on the vehicle dynamics control system.As a representative product of vehicle dynamic stability control technology,electronic stability control(ESC)is recognized as another breakthrough after the anti-locked braking system(ABS).The system uses the direct yaw moment control as the core to improve the vehicle stability by reducing the engine torque or independently controlling the braking force acting on the tire.However,the additional yaw moment generated by the braking method is at the expense of reducing the vehicle speed,which not only reduces the driving ability,but also gives the driver a significant sense of intervention.In contrast,torque vectoring(TV)control of distributed drive EVs produces additional yaw moments by independently controlling the drive or braking torque on the drive wheels.Unlike the ESC system,TV controller can improve the dynamic performance of the vehicle according to the driver's driving intention without significantly reducing the vehicle speed,providing the driver with a high-quality driving experience.However,how to give full play to the advantages of distributed drive EVs in improving vehicle dynamics performance still faces enormous challenges:(1)State observer design problems for uncertain nonlinear vehicle systems under extreme conditions.In view of the nonlinear dynamic characteristics exhibited by the vehicle during driving,although the nonlinear observer method can obtain a good estimation effect,the uncertainty of the vehicle nonlinear system and requirements for vehicle state estimation accuracy under extreme conditions is considered.How to ensure the stability of the observer and the accuracy of vehicle state estimation under extreme conditions is a difficult problem in designing the observer.(2)Considering the impact of differences in driving skills on driving safety,how to simulate the “sensing-decision-execution” mechanism of professional drivers,revealing the dynamic mechanism of professional drivers to dynamically adjust the vehicle's motion state,and refining the control targets that meet the driver's steering intentions,establishing a control architecture that combines the operational characteristics of the driver with the vehicle dynamics system requires further study.(3)Coordinated control of lateral and longitudinal motion of vehicles with uncertain,nonlinear dynamics.Under extreme conditions,the tire force easily enters the nonlinear saturation region,and the coupling and saturation characteristics of the tire lateral and longitudinal forces cause the system to fail to provide sufficient additional yaw moment.How to realize the coordinated control of lateral and longitudinal motion of the vehicle by adjusting the longitudinal force of the tire,and establish a control algorithm which is robust to model error and parameter uncertainty,and to enhance the dynamic performance of the vehicle to the greatest extent,which needs to be solved.Focusing on the above difficult problems,this paper has carried out five researches based on vehicle state estimation and TV control from the two aspects of “driving assistance” and “cooperative control of lateral and longitudinal motion of the vehicle”:(1)An eight-degree-of-freedom(8DOF)vehicle model capable of describing the nonlinear dynamic characteristics of real vehicles was established,which provided a simulation platform for the algorithm verification of distributed drive EVs.To facilitate the development of the control strategy,the above 8DOF vehicle model was simplified,and a three-degree-of-freedom(3DOF)vehicle model oriented to control strategy was established.The accuracy of the vehicle model was verified by comparison with experimental data.(2)A nonlinear vehicle state observer based on the Uni Tire model was proposed.Aiming at the design problem of state observers for uncertain nonlinear vehicle systems under extreme conditions,the Uni Tire model was used to estimate the lateral and longitudinal tire forces.The estimated values of lateral and longitudinal acceleration were obtained by the 3DOF vehicle model.Based on this,the estimated error of the lateral and longitudinal acceleration was used as a feedback term,the lateral and longitudinal vehicle speed was estimated using known vehicle signals.Considering that measurement noise,sensor drift error and model error may cause the observation system to diverge,the input-to-state stability(ISS)theory was used to analyze the sufficient conditions for the bound error of the estimation error,and the range of the observer gain was given.(3)A TV control strategy based on the operational characteristics of professional drivers was proposed.1)To reveal the vehicle dynamics mechanism of the professional driver adjusting the vehicle's motion state in the corner,the driver's operational characteristic test was designed.By analyzing the control methods of the accelerator,brake and steering wheel during the turning process,the relationship between the professional driver's operation and the steering characteristics of the vehicle was obtained,and the control target based on the professional driver's operating characteristics was formulated.2)To achieve decoupling of lateral and longitudinal dynamic systems,a hierarchical control architecture was employed.For the robust control problem caused by model error and estimation error,the upper controller applied the sliding mode control(SMC)theory to calculate the additional yaw moment required to follow the control target.To eliminate the chattering phenomenon of traditional SMC,an adaptive second-order sliding mode control(ASOSM)algorithm capable of outputting smooth control was designed.3)For the cooperative control problem of lateral and longitudinal motion of the vehicle,an optimal torque distribution strategy that could take into account the lateral and longitudinal stability of the vehicle was proposed.The additional yaw moment control error,the tire working load and the driver's longitudinal demand torque were weighted and combined.By analyzing the longitudinal dynamic coupling mechanism,the weight self-tuning strategy based on tire slip ratio was designed and the optimization was derived.The analytical expression of the problem realized the coordinated control of the lateral and longitudinal motion of the distributed drive EV.(4)Simulation verification of TV control strategy based on professional driver operating characteristics.Firstly,to verify the advantages of the TV control strategy in improving the steady-state steering characteristics and transient steering characteristics of the vehicle,the TV control strategy was simulated in steady-state and angular pulse conditions.On this basis,to prove the TV control strategy based on the professional driver's operating characteristics,not only could the vehicle's steering stability be improved,but also the driver's operating load could be alleviated.Taking the vehicle with neutral steering characteristics as the benchmark,the dynamic performance of the vehicle with the TV control strategy and the neutral steering vehicle was compared in the double lane change operation.(5)Road test of nonlinear vehicle state observers and TV control strategies.To further realize the engineering application of the algorithm,the Dongfeng E70 test sample vehicle was built and the real vehicle control program was developed.The update step size of the algorithm was 50 ms,and the effectiveness of the constructed observer and TV control algorithm was verified in the extreme conditions.The test results showed that the TV control based on the driver's operating characteristics could reduce the driver's operating load,and balanced the lateral and longitudinal stability of the vehicle.This provides an algorithmic guarantee for the dynamic control of distributed drive EVs under production conditions. |
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