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Hydraulic retarder has been widely applied on military vehicles and heavy commercial vehicles because of it could provide great brake torque and has lasting working time [1]. In order to reduce driver's frequent actions in braking process and prevent hydraulic retarder system from overheating, it is need to apply constant braking torque control, this control target has a strict requirement to hydraulic control system design. Many parameters often require repeated test to determine, which increases the R&D cost and extends the research cycle. This paper tries to find a time-efficient research method of hydraulic retarder control system through studying on a heavy military vehicle hydraulic retarder system. Hydraulic retarder model is set up through test data. The hydraulic control system is built based on AMESim. Controller model is set up based on PID control. The whole vehicle brake model is built based on MATLAB/Simulink.

Vehicle auxiliary braking system is very significant to the brake safety. The eddy current retarder (ECR) has a good braking performance, but the braking torque would fade under high speed domain. In the contrary, the regenerative brake (RGB) could provide a satisfied braking performance in high speed domain. However, the braking torque in low speed domain is insufficient. This paper proposed a novel concept of the integrated energy-recuperation retarder (IEER), which would take advantage of the merits of both the ECR and the RGB to have a steady braking performance in all-speed domain. The IEER integrates the structures of rotary eddy current retarder (RECR) and the RGB, both of which share a stator. Braking torque of the IEER produced by stator core and armature-windings can stack together, and therefore the IEER can provide greater braking torque than the RECR. Besides, the IEER can recover electric energy from armature-windings.

With the rapid development of the logistics and transportation industry, heavy-duty trucks play an increasingly important role in social life. However, due to the characteristics of large cargo loads, high center of mass and relatively narrow wheelbase, the driving stability of heavy trucks are poor, and it is easy to cause rollover accidents under high-speed driving conditions, large angle steering and emergency obstacle avoidance. To improve the roll stability of heavy trucks, it is necessary to design an active anti-rollover control system, through the analysis of the yaw rate and the load transfer rate of the vehicle, driving states can be estimated during the driving process. Under the intervention of the control system, the lateral transfer rate of heavy trucks can be reduced to correct the driving posture of the vehicle body and reduce the possibility of rollover accidents.

When driving in mountainous areas, vehicles often encounter downhill conditions. To ensure safe driving, it is necessary to control the speed of vehicles. For internal combustion engine vehicles, auxiliary brake such as engine brake can be used to alleviate the thermal load caused by the continuous braking of the friction brake. For battery electric vehicles (BEVs), regenerative braking can be used as auxiliary braking to improve brake safety. And through regenerative braking, energy can be partly converted into electrical energy and stored in accumulators (such as power batteries and supercapacitors), thus extending the mileage. However, the driver's line of sight in the mountains is limited, resulting in a certain degree of blindness in driving, so it is impossible to fully guarantee the safety and energy saving of downhill driving.

This paper proposed a model predictive control(MPC) based car-following control strategy for electric vehicles considering comfort, in order to improve the comfort of the car-following control system of electric vehicles. The MPC algorithm is improved in the following three aspects to improve the comfort: Firstly, a five-state longitudinal car-following model is adopted, so that the MPC algorithm can optimize the acceleration and acceleration change rate of the ego vehicle. Secondly, for the weight coefficients of the output vector and the input vector of the objective function, the fixed weight coefficients are changed into variable weight coefficients by the way of Nash equilibrium game, so that the control system can improve the weight of the parameters used to control the comfort under suitable driving conditions.

Braking energy recovery is an important method for Battery Electric Vehicle (BEV) to save energy and increase driving range. The vehicle braking system performs regenerative braking control based on driver operations. Different braking operations have a significant impact on energy recovery efficiency. This paper proposes a method for planning the braking process of a BEV based on the Intelligent Vehicle Infrastructure Cooperative System (IVICS). By actively planning the braking process, the braking energy recovery efficiency is improved. Vehicles need to decelerate and brake before entering a curve. The IVICS is used to obtain information about the curve section ahead of the vehicle's driving route. Then calculating the reference speed of the curve, and obtaining the vehicle's braking target in advance, so as to actively plan the vehicle braking process.

Focusing the vehicle riding safety and global environmental problems, plenty of solutions on vehicle braking systems appeals during the recent period. Criteria and standards set up for commercial vehicles which should have equipped assisted braking systems were established by amounts of governments. Since eddy current retarders plays an important role in the area of assisted braking system, this article presents an energy-recuperation retarder, which is parallel connected with the driveline through a planet gear system. This paper offers a particular Energy-Recuperation Eddy Current Retarder (ERECR) system with a pedal control system and its characteristics is presented, either. Initially, the constitution of the energy-recuperation eddy current retarder system is established whereas the working principle of the energy-recuperation eddy current retarder is presented by modeling the system and simulation.

For cooperative adaptive cruise control (CACC) system, a robust following control algorithm based on fuzzy PID principle is adopted in this paper. Firstly, a nonlinear vehicle dynamics model considering the lag of driving force and acceleration constraints was established. Then, with the vehicle’s control hierarchic, the upper controller takes the relative speed between vehicles and the spacing error as inputs to output the following vehicle's target acceleration, while the lower controller takes the target acceleration as inputs and the throttle opening and brake master cylinder pressure as outputs. For the setting of target spacing, this paper additionally considers the relative speed between vehicles and the acceleration of the front vehicle. Through testing, compared with the traditional variable safety distance model, the average distance reduces by 5.43% when leading vehicle is accelerating, while increases by 2.74% in deceleration.

Regenerative braking is an effective technology to extend the driving range of electrified vehicles by recovering kinetic energy from braking. This paper focuses on the design of the regenerative braking control strategy for a commercial vehicle which requires significantly larger braking power than passenger cars. To maximize the energy recovery while ensuring the braking efficiency of the vehicle and its braking safety, this paper proposed a fuzzy logic strategy for regenerative braking control, and a feasibility study was conducted for an electric van. The work includes in three steps. Firstly, state variables that significantly affect regenerative braking performance, i.e., vehicle speed, battery State-of-Charge (SOC), and braking intensity, are identified based on mathematical modelling of the vehicle system dynamics in braking maneuver.

Road simulation experiment in laboratory is a most important method to enhance the design quality of vehicle products. Presently, two main control techniques for road simulation—remote parameter control (RPC) and minimum variance adaptive control—are both defective: the former becomes an open-loop control after generating the drive signals, however the latter is essentially a kind of gradual control. To realize the closed-loop control and increase the control quality, this article brings forward a PID open-closed loop control method. Firstly taking the original road simulator as a group to identify, a nonlinear autoregressive moving average (NARMA) model was built with the dynamic neural network. Subsequently, this plant model was used to build the open-closed loop control system mentioned above. In the closed-loop a discrete PID controller was introduced to stabilize the system, while a P-type iterative learning control (ILC) was adopted to increase the control quality.

The cabin air temperature increases quickly and can reach 80°C when the vehicle parks in the summer sunlight which has the bad influence on the occupants entering comfort. Some luxury vehicles, like Audi A8[1], reduce the internal temperature through operating air-condition in advance or using on-board battery to drive the cabin ventilator, which requires relatively complex control system and limits the system's operating time because of energy consumption. This research adopts the solar wing as the ventilation power supply and accomplishes the cabin real-time heat rejection by achieving the steady air circulation for both inside and outside environment. First, the static thermal transfer model of the crew cabin is established. Then, on the basis of the parameters of the prototype ventilation pipe, the ventilation model for the outside circulation is built.

In order to ensure driving safety, heavy vehicles are often equipped with hydraulic retarder, which provides sustained, stable braking torque and converts the vehicle kinetic energy into heat taken away by the cooling system when traveling on a long downhill. The conventional hydraulic retarder braking torque is modulated by adjusting the liquid filling rate, which leads to slow response and difficult control. In this paper, a new kind of magnetorheological (MR) fluid hydraulic retarder is designed by replacing the traditional transmission oil with MR fluid and arranging the excitation coils outside the working chamber. The braking torque can be controlled by the fluid viscosity of MR fluid with the variation of magnetic field. Compared with the traditional hydraulic retarder, the system has the advantages of fast response, easy control and high adjustment sensitivity.

Plenty of dust particles which are generated when a sweeping vehicle is dumping harm to workers' health. In the study, the designed vacuum dust control system could effectively capture easily raised dust particles in the air in the premise of not impacting the dumping process so as to improve the unloading work environment. Firstly, longitudinal motion trajectory model of dust particles in the dumping process is established. Based on the side collision probability model of dust particles, lateral velocity distribution of dust particles is obtained. What's more, the scope of lateral dust particles is determined. Taking into account coupling of the dust control system and the working state of the vehicle, the suction mouth is arranged at the edge on the outside of hatch cover. Centrifugal horizontal dust removal system designed in the research is fixed in the middle of the filter cover part and discharging hatch cover area.

The tracked vehicle with a fully hydraulic driving system, which has a strong traveling performance of passing and mobility ability in the complex terrain, is a typical system of mechanical-electrical-hydraulic integration. At the same time, for the good low-speed stability of the hydraulic system, this vehicle is widely applied in most engineering projects. However, for the complexity and unpredictability of the motion state in the complex environment and the power matching of the driving system, the driving path of the tracked vehicle with hydraulic driving is difficult to control. Moreover, for the complicated interaction between mechanics, the establishment of the mathematical model is much more complex, and the traditional mechanics-control and hydraulic-control co-simulation can not accurately simulate this physical phenomenon. The kinematic and dynamics characteristics of the tracked vehicle are studied firstly, and the dynamics model is built.

The vehicle engine exhaust wastes heat. For the conventional scheme, the hot-end of the thermoelectric module is connected with the exhaust pipe, while the cold-end is cooled through the vehicle engine cooling cycle. The variation of vehicle engine operating conditions brings the instability of the hot-end temperature, which affects the power generation performance of thermoelectric materials and increases the damage risk to the thermoelectric materials caused by the high temperature. This research adopts the heat transfer oil circulation as the intermediate fluid to absorb the dynamic heat flux of the vehicle engine exhaust so as to release the heat steadily to the hot-end of the thermoelectric module. The thermal characteristics of the target diesel vehicle engine exhaust gas are evaluated based on the experimental data firstly.

The development of intelligent transportation improves road efficiency, reduces automobile energy consumption, and improves driving safety. The core of intelligent transportation is the two-way information interaction between vehicles and the road environment. At present, road environmental information can flow to the vehicle, while the vehicle’s information rarely flows to the outside world. The electronic throttle and electronic braking systems of some vehicles use sensors to get the state of the accelerator and brake pedal, which can be transmitted to the outside environment through technologies such as the Internet of Vehicles. But the Internet of Vehicles technology has not been widely used, and it relies on signal sources, which is a passive way of information acquisition. In this paper, an active identification method is proposed to get the vehicle pedal on-off state as well as the driver’s operation behavior through existing traffic facilities.