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A braking force distribution strategy in integrated braking system composed of the main braking system and the auxiliary braking system based on braking pad wear control and hitch force control under non-emergency braking condition is proposed based on the Electronically Controlled Braking System (EBS) to reduce the difference in braking pad wear between different axles and to decrease hitch force between tractors and trailers. The proposed strategy distributes the braking force based on the desired braking intensity, the degree of the braking pad wear and the limits of certain braking regulations to solve the coupling problems between braking safety, economical efficiency of braking and the comfort of drivers. Computer co-simulations of the proposed strategy are performed.

Research of Adaptive Cruise Control (ACC) is an important issue of intelligent vehicle (IV). As we all known, a real and experienced driver can control vehicle's speed very well under every traffic environment of ACC working. So a direct and feasible way for establishing ACC controller is to build a human-like longitudinal control algorithm with the simulation of driver behavior of speed control. In this paper, a novel fuzzy self-tuning control algorithm of ACC is established and this controller's parameters can be tuned on-line based on the evaluation indexes that can describe how the driver consider the quality of dynamical characteristic of vehicle longitudinal dynamics. With the advantage of the controller's parameter on-line self-tuning, the computational workload from matching design of ACC controller is also efficiently reduced.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

A high-precision steady state tire model is critical in the tire and vehicle matching research. For the moment, the popular Magic Formula model is an empirical model, which requires the pure and combined test data to identify the model parameters. Although MTS Flat-trac is an efficient tire test rig, the long test period and high test cost of a complete tire model tests for handling are yet to be solved. Therefore, it is necessary to explore a high accuracy method for predicting tire complex mechanical properties with as few test data as possible. In this study, a method for predicting tire combined slip characteristics from pure cornering and pure longitudinal test data has been investigated, and verified by comparing with the test data. Firstly, the prediction theory of UniTire model is introduced, and the formula for predicting combined slip characteristics based on constant friction coefficient is derived.

Vehicle lane keeping system is becoming a new research focus of drive assistant system except adaptive cruise control system. As we all known, vehicle lateral dynamics show strong nonlinear and time-varying with the variety of longitudinal velocity, especially tire’s mechanics characteristic will change from linear characteristic under low speed to strong nonlinear under high speed. For this reason, the traditional PID controller and even self-tuning PID controller, which need to know a precise vehicle lateral dynamics model to adjust the control parameter, are too difficult to get enough accuracy and the ideal control quality. Based on neural network’s ability of self-learning, adaptive and approximate to any nonlinear function, an adaptive PID control algorithm with BP neural network self-tuning online was proposed for vehicle lane keeping.

The slip ratio of vehicle driving wheels is easily beyond a reasonable range in the complex and changeable driving conditions. In order to achieve the adaptive acceleration slip regulation of four-wheel driving (4WD) vehicle, a fuzzy control strategy of Automatic Drive Train Management (ADM) system based on road situation identification was proposed in this paper. Firstly, the influence on the control strategy of ADM system was analyzed from two aspects, which included the different road adhesion coefficients and the vehicle’s ramp driving state. In the meantime several quantitative expressions of relevant control parameters were derived. Secondly, the fuzzy logic control algorithm was adopted to design a road situation identification subsystem and a ramp driving state identification subsystem respectively. The former was based on the μ-S curve model, and the latter was based on the vehicle driving equilibrium equation.

A program of integrated electro-hydraulic braking system is proposed, and its structural composition and working principle are analyzed. According to the structural and mechanical characteristics of all key components, through some reasonable assumptions and simplifications, a motor, a brake master cylinder, four brake wheel cylinders, solenoid valves and an ESP (Electronic Stability Program) algorithm model is set up and simulations of typical braking conditions are carried out based on the Matlab/Simulink. Finally, after the assembly of each sub-model is complete and combining a vehicle which is set up in CarSim software environment, simulation tests and comprehensive performance analysis of the active safety stability control for a vehicle in double lane change and single lane change situations are carried out respectively. According to the dynamic characteristic curves of system, the effects of different structural and control parameters on braking performance are analyzed.

The new control algorithm for parallel hybrid electric vehicle is presented systematically, in which engine operation points are limited within higher efficient area by the control algorithm and the state of charge (SOC) is limited in a range in order to enhance the batteries' charging and discharging efficiency. In order to determine the ideal operating point of the vehicle's engine, the control strategy uses a lookup table to determine the torque output of the engine. The off-line simulation model of parallel HEV power train is developed which includes the control system and controlled objective (such as engine, electric motor, battery pack and so on). The results show that the control algorithm can effectively limite engine and battery operation points and much more fuel economy can be achieved than that of conventional one.

Direct yaw moment control can maintain the vehicle stability in critical situation. For four-wheel independently driven (4WD) electric vehicle with in-wheel motors (IWMs), direct yaw moment control (DYC) can be easily achieved. A fairly accurate calculation of the required yaw moment can improve vehicle stability. A novel sliding mode control (SMC) technique is employed for the motion control so as to track the desired vehicle motion, which is it for different working circumstances compared to the well-used traditional DYC. Through the weighted least square algorithm, the lower controller is used to determine the torque properly allocated to each wheel according to the desired yaw moment. Several actuator constraints are considered in the control strategy. In addition, a nonlinear tire model is utilized to improve the accuracy of tire lateral force estimation. Then, simulations are carried out and the values of vehicle states are compared.

Adaptive cruise control system with lane change assistance (LCACC) is a novel advanced driver assistance system (ADAS), which enables dual-target tracking, safe lane change, and longitudinal ride comfort. To design the personalized LCACC system, one of the most important prerequisites is to identify the driver’s individualities. This paper presents a real-time driver behavior characteristics identification strategy for LCACC system. Firstly, a driver behavior data acquisition system was established based on the driver-in-the-loop simulator, and the behavior data of different types of drivers were collected under the typical test condition. Then, the driver behavior characteristics factor Ks we proposed, which combined the longitudinal and lateral control behaviors, was used to identify the driver behavior characteristics. And an individual safe inter-vehicle distances field (ISIDF) was established according to the identification results.

Adaptive cruise control is one of the key technologies in advanced driver assistance systems. However, improving the performance of autonomous driving systems requires addressing various challenges, such as maintaining the dynamic stability of the vehicle during the cruise process, accurately controlling the distance between the ego vehicle and the preceding vehicle, resisting the effects of nonlinear changes in longitudinal speed on system performance. To overcome these challenges, an adaptive cruise control strategy based on the Takagi-Sugeno fuzzy model with a focus on ensuring vehicle lateral stability is proposed. Firstly, a collaborative control model of adaptive cruise and lateral stability is established with desired acceleration and additional yaw moment as control inputs. Then, considering the effect of the nonlinear change of the longitudinal speed on the performance of the vehicle system.

Tire-road friction condition is crucial to the safety of vehicle driving. The emergence of autonomous driving makes it more important to estimate the friction limit accurately and at the lowest possible excitation. In this paper, an early detection method of tire-road friction coefficient based on pneumatic trail under cornering conditions is proposed using an intelligent tire system. The previously developed intelligent tire system is based on a triaxial accelerometer mounted on the inner liner of the tire tread. The friction estimation scheme utilizes the highly sensitive nature of the pneumatic trail to the friction coefficient even in the linear region and its approximately linear relationship with the excitation level. An indicator referred as slip degree indicating the utilization of the road friction is proposed using the information of pneumatic trail, and it is used to decide whether the excitation is sufficient to adopt the friction coefficient estimate.

Starting control has become a troublesome issue in the developing field of the control system for heavy-duty trucks, due to the complexity of vehicle driving and the variability of driver's intention. The too fast clutch engagement may result in serious impact, influence on the comfort and fatigue life, and even the engine flameout, while the too slow clutch engagement may lead to long time of friction, the increased temperature, and accelerated wear of friction pair, as well as influence on the power performance and fatigue life[1]. Therefore, the key technique of starting control is clutch engagement control, for which the fuzzy PID based optimization of starting control for AMT clutch is proposed, with the pneumatic AMT clutch of heavy-duty trucks as the research object.

The powers generated by the skidding and slipping of a vehicle in unit time during driving are referred to as parasitic power. It has significant effects on wear on the tires, service life, and overall efficiency. However, existing methods to calculate parasitic power expressions that are not solvable in some cases, the reasonableness of the results of their calculations cannot be verified by experiments and the parameters of the loader cannot be calculated during the design of the vehicle. In this paper, we systematically analyze the mechanism of generation of parasitic power based on the differences in the radii of the tires of loaders. We innovatively propose a theoretical calculation method to calculate the wheel circumference parasitic work during the design of the loader. The results of experiments show that errors between the theoretical and experimental values of the wheel circumference parasitic work calculated under various working conditions were smaller than 5%.

A general principle scheme of IEHB (Integrated Electro-Hydraulic Brake system) is proposed, and the working principle of the system is simply introduced in this paper. Considering the structure characteristics of the hydraulic control unit of the system, a kind of time-sharing control strategy is adopted to realize the purpose of independent and precise hydraulic pressure regulation of each wheel brake cylinder in various brake conditions of a vehicle. Because of the strong nonlinear and time varying characteristics of the dynamic brake pressure regulation processes of IEHB, its comprehensive brake performance is mainly affected by temperature, humidity, load change, the structure and control parameters of IEHB, and so on.

In order to improve the vehicle economy of electric vehicles, this paper first analyzes the energy-saving mechanism of electric vehicles. Taking the energy consumption of the deceleration process as a starting point, this paper deeply analyzes the energy consumption of the deceleration process under several different control modes by the test data, so as to obtain two principles that should be followed in energy-saving control strategy. Then, an intelligent deceleration energy-saving control strategy by getting the forward vehicle information is developed. The overall architecture of the control strategy consists of three parts: information processing, target calculation and torque control. The first part is mainly to obtain the forward vehicle information from the perception systems, and the user's habits information from big data, and this information is processed for the next part.

The calibration of the electronic throttle unit and the pedal unit was made. Based on it, an electronic control system of electronic throttle was designed and installed on a 4G18 engine. Engine experiment was made especially for its transient working condition. Engine performance at transient working condition was investigated. The test results indicate that the optimum way of opening the throttle valve is to open the throttle valve to the target location at once, when 4G18 engine transit from 2000r/min to 3000r/min without load. And its optimum calibration for the electronic throttle control unit is made based on the test results. The control system, the experiment, the test results and the calibration were introduced in this paper.

A new lateral stability control method, which is based on vehicle sideslip angle and tire cornering stiffness estimation, is proposed to improve the lateral stability of the four-in-wheel-motor-driven electric vehicle (FIWMD-EV) in this paper. Through the lateral tire force information, vehicle sideslip angle can be estimated by the extended kalman filter (EKF). Using the estimated vehicle sideslip angle, tire cornering stiffness can be also estimated by forgetting factor recursive least squares (FFRLS). Furthermore, combining with the vehicle dynamics model, an adaptive control target model is proposed with the information on vehicle sideslip angle and tire cornering stiffness. The new lateral stability control system uses the direct yaw moment control (DYC) based on dynamic sliding mode is proposed. The performance and effectiveness of the proposed vehicle state estimation and lateral stability control system are verified by CarSim and Simulink cosimulation.

In the past decades, the stability of vehicles has been improved significantly by use of variety of chassis control systems such as Antilock Braking System (ABS), Electric Stability Program (ESP) and Active Front Steering (AFS). Recently, in order to further improve the performance of vehicles, more and more researches are focused on the integration control of multiple degrees of freedom of vehicle dynamic. However, in order to control multiple degrees of freedom simultaneously, the nonlinear problems caused by the coupling between different degrees of freedom have to be solved, which is always a difficult task. In this paper, a three-degrees-of-freedom single track vehicle model, in which some nonlinear terms are considered, is built firstly. Then, the nonlinear model is processed by the fuzzy technique and the T-S fuzzy model is designed.

A vehicle-mounted anti-vibration system is designed to semi-actively reduce accelerations acting on vibration isolation platform under different road conditions. To provide the basis for optimal anti-vibration design, the kinematics and dynamics of the platform are analyzed to investigate the relationship between leg length, strength, the platform position and vibration properties. As the platform is fixed on vehicle, a combined vehicle-platform model is necessary for verifying the performance and applying some suitable control algorithms. Also, typical digital testing roads will be built using road load spectrum. To optimize the platform parameters, especially stiffness and damping, an active control system is designed at first. An anti-vibration system including a semi-active inerter is designed to match the control forces which are calculated from the above active system.