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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.

With the development of intelligent and electric vehicles, higher requirements are put forward for the active braking and regenerative braking ability of the braking system. The traditional braking system equipped with vacuum booster has difficulty meeting the demand, therefore it has gradually been replaced by the integrated braking system. In this paper, a novel Integrated Braking System (IBS) is presented, which mainly contains a pedal feel simulator, a permanent magnet synchronous motor (PMSM), a series of transmission mechanisms, and the hydraulic control unit. As an integrative system of mechanics-electronics-hydraulics, the IBS has complex nonlinear characteristics, which challenge the accurate pressure control. Furthermore, it is a completely decoupled braking system, the pedal force doesn’t participate in pressure-building, so it is necessary to precisely identify driver’s braking intention.

The Electronic Stability Program (ESP), as a key actuator of traditional automobile braking system, plays an important role in the development of intelligent vehicles by accurately controlling the pressure of wheels. However, the ESP is a highly nonlinear controlled object due to the changing of the working temperature, humidity, and hydraulic load. In this paper, an accurate pressure control strategy of single wheel during active braking of ESP is proposed, which doesn’t rely on the specific parameters of the hydraulic system and ESP. First, the structure and working principle of ESP have been introduced. Then, we discuss the possibility of Pulse Width Modulation (PWM) control based on the mathematical model of the high-speed switching valve. Subsequently, the pressure building characteristics of the inlet and outlet valves are analyzed by the hardware in the Loop (HiL) experimental platform.

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.

This paper presents an integrated method for rapid modeling, simulation and virtual evaluation of the interface pressure between driver human body and seat. For simulation of the body-seat interaction and for calculation of the interface pressure, besides body dimensions and material characteristics an important aspect is the posture and position of the driver body with respect to seat. In addition, to ensure accommodation of the results to the target population usually several individuals are simulated, whose body anthropometries cover the scope of the whole population. The multivariate distribution of the body anthropometry and the sampling techniques are usually adopted to generate the individuals and to predict the detailed body dimensions. In biomechanical modeling of human body and seat, the correct element type, the rational settings of the contacts between different parts, the correct exertion of the loads to the calculation field, etc., are also crucial.

In order to solve the coupling problems between braking safety, economical efficiency of braking and the comfort of drivers, a braking control strategy based on Electronically Controlled Braking System (EBS) and intelligent network technology under non-emergency braking conditions is proposed. The controller utilizes the intelligent network technology’s characteristics of the workshop communication to obtain the driving environment information of the current vehicle firstly, and then calculate the optimal braking deceleration of the vehicle based on optimal control method. The strategy will distribute the braking force according to the ideal braking force distribution condition based on the EBS according to the braking deceleration; the braking force will be converted to braking pressure according to brake characteristics. Computer co-simulations of the proposed strategy are performed, the strategy is verified under different initial speeds.

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.

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.

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.

A novel non-destroy repeatable-use impact theory based total cylinder sampling system has been established. This system is mainly composed of a knocking body and a sampling valve. The knocking body impacts the sampling valve with certain velocity resulting in huge force to open the sampling valve and most of the in-cylinder gas has been dumped to one sampling bag for after-treatment. The feasibility and sampling response characteristics of this impact theory based total cylinder sampling system were investigated by engine bench testing. Within 0 to 35°CA ATDC (Crank Angle After Top Dead Center) sample timing 50 percent to 80 percent of in-cylinder mass would be sampled, which was a little less compared with the traditional system. The half decay period of pressure drop was 10 to 20 degrees crank angle within 0 to 60°CA ATDC sample timing, which was about 2-3 times of the traditional system.

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.

As bottom layer actuator for the AEB system, the active brake system and the brake force control of tractor-semitrailer have been the hot topics recently. In this paper, a set of active pneumatic brake system was designed based on the traditional brake system of tractor-semitrailer, which can realize the active brake of the vehicle under necessary conditions. Then, a precise mathematical model of the active pneumatic brake system was built by referring the flow characteristics of the solenoid valve, and some tests were implemented to verify the accuracy and validity of the active brake system model. Based on the model, an active pneumatic brake pressure control strategy combining the feedforward and feedback controlling modes was designed. By generating the PWM control signal, it can precisely control the desired wheel cylinder brake pressure of the active brake system. Finally, the brake pressure control strategy was validated both by simulation tests and bench tests.

It is generally considered that the material properties of foam are the most important factors in vehicle seat, which affect the human-seat interface pressure. Therefore, only the role of foam is usually considered when the finite element method is used to simulate the human-seat interface pressure. In this paper, the mechanical properties and the modeling method of commonly used seat cover material were studied. The models of the seat with and without cover were established respectively according to the real-vehicle seat geometric data, and the human-seat interface pressure was simulated after the seat and human model consisting of bones, soft tissue and skin were assembled. The simulation result was compared with the actual measurement results from test, which verified the accuracy of the simulation and the role of seat cover in the human-seat interface pressure simulation.

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.