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As an off-road racing car, driving conditions for a Baja racing car are particularly complex. Extreme working conditions such as deep pits and rocky roads have put higher demand on structural strength and frame safety. To solve this problem, extreme working conditions are first studied to check the safety of the steel tube frame of Baja racing cars. Secondly, based on Noise, Vibration, and Harshness (NVH) to explore the frame's characteristics, analyze the frame's six-order mode, make the corresponding optimization, and solve the resonance problem caused by engine excitation and other factors. Finally, the natural frequency of the frame is measured to verify the effectiveness of the NVH characteristic optimization results, and it is found that the experimental results match the theoretical values. The theoretical analysis results are mainly based on ANSYS software's static and modal analysis.

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.

Dynamic modeling and state estimation are significant in the trajectory tracking and stability control of the intelligent vehicle. In order to meet the requirement of the stability control of the eight-in-wheel-motor-driven intelligent vehicle, a full vehicle dynamics model with 12 degrees of freedom, including the longitudinal, lateral, yaw and roll motion of the body, and rotational motion of 8 wheels, is established for the research of the intelligent vehicle in this paper. By simulation with MATLAB/SIMULINK and by comparison with the TruckSim software, the reliability and practicality of the dynamics model are verified. Based on the established dynamics model, an extended Kalman filter (EKF) state observer is proposed to estimate the vehicle sideslip angle, roll angle and yaw rate, which are the key parameters to the stability control of the intelligent vehicle.

This paper presents a Driver-In-the-Loop (DIL) bench test system for development of ESC controller. The real-time platform is built-up based on NI/PXI system and the real steering/throttle/braking actuator. In addition, the CarSim provides the vehicle model and the animator for virtual driving environment. A hierarchical ESC controller is proposed in MATLAB/Simulink then download into PXI. In the upper motion controller, the sliding mode theory is adopted and the logic threshold algorithm is used in the lower slip controller. Finally, ESC test is implemented under typical conditions by DIL and Model-In-the-Loop (MIL). The results show that, DIL could make up the shortage of driver model which can’t accurately simulate the emergency response of real driver. Therefore, DIL test could verify the ESC controller more accurately and effectively with considering the human-vehicle-road environment.

Fluid auxiliary braking devices can provide braking torque through hydraulic damping, fluid auxiliary braking devices can also convert vehicular inertia energy into transmission fluid heat energy during the braking, which can effectively alleviate the work pressure of the main brake. Traditional hydraulic auxiliary braking devices use transmission fluids to transmit torque, however, there is a certain lag effect during the braking. The magnetorheological fluid (MR fluid) can also be used to transmit torque because it has the advantages of controlling braking torque linearly and responding fast to the magnetic field changed. The temperature of MR fluid will increase when the vehicle is engaged in continuous braking. MR fluid temperature changes will cause a bad influence on the efficiency stability of auxiliary braking.

Mountain road winding and bumpy, traffic accidents caused by speeding frequently happened, mainly concentrated on curves. The present curve warning system research are based on Charge-coupled Device, but the existing obstacles, weather , driving at night and road conditions directly affect the accuracy and applicability. The research is of predictability to identify the curves based on the geographic information and can told the driver road information and safety speed ahead of the road according to the commercial vehicle characteristic of load, and the characteristics of the mass center to reduce the incidence of accidents. In this paper, the main research contents include: to estimate forward bend curvature through the node classification method based on the digital map.

Studies show that driving in foggy environment is a security risk, and when driving in foggy environment, the drivers are easy to accelerate unconsciously. The safety information prompted to the driver is mainly from fog lights, road warning signs and the traffic radio. In order to increase the quality of the safety tips to prevent drivers from unintended acceleration and ensure the security of driving in foggy environment, the study proposes a safety speed assessment method for driving in foggy environment, combining the information of driving environment, vehicle’s speed and the multimedia system. The method uses camera which is installed on the front windshield pillar to collect the image about the environment, and uses the dark channel prior theory to calculate the visibility. And by using the environment visibility, the safety speed can be calculated based on the kinematics theory. And it is appropriate for vehicles which have different braking performance.

The cooling system with two fans is generally driven by electrical motors in the small cars. Compared with the traditional cars, heavy duty trucks have the larger heat dissipation power of cooling system. The motors power consumption of dual fans will be larger and the two electrical motors will occupy a large space in the engine cabin. Hydrostatic drive refers to the cooling fan is driven by hydraulic motor, but it has the low transmission efficiency. According to the engine water temperature value and the actual working status of the hydraulic system, the actual speed of cooling fan can be controlled by the computer, which guarantees the normal working water temperature of the engine. Hydrostatic drive is generally applied to heavy vehicles, engineering machinery and excavators as driving source of cooling fan which contains the advantages of large output power, overload protection, continuous speed regulation and flexible space arrangements.

The heavy duty trucks have large engine power and drive continuously in mountainous area, so the heat dissipation of engine is very important. In the traditional cooling system with fixed transmission ratio fan, the cooling capacity is insufficient and the engine is easy to be over-heated when the engine is working in low speed and heavy load conditions. Owning to the bigger size of electric motor compared to the hydraulic motor, it is not suitably applied to the heavy duty trucks. Contrasted with the electric motor, the hydraulic drive cooling system is widely applied in heavy duty trucks due to smaller size, larger power, continuous speed modulation and flexible installation location. However, the low transmission efficiency of the pump-motor system results in high power consumption of the cooling system. In this paper, the mathematical and simulation model of hydraulic-driven fan cooling system is established for the specific engine.

The hydraulic retarder, which is an auxiliary brake device for enhancing traffic safety, has been widely used in kinds of heavy commercial vehicles. When the vehicle equipped with the retarder is traveling in non-braking state, the transmission loss would be caused because of the stirring air between working wheels of the rotor and the stator no matter if the retarder connects in parallel or in series with the transmission [1]. This paper introduces an elaborate hydraulic retarder air-friction reduction system (AFRS) which consists of a vacuum generating module and pneumatic control module. AFRS works to reduce the air friction by decreasing the gas density between working wheels when the retarder is in non-braking state. The pneumatic control model of hydraulic retarder is built first. Then various driving conditions are considered to verify the performance of the AFRS. The stability of the AFRS is analyzed based on the complete driveline model.

On road simulation, both the traditional iterative method based on frequency response function (FRF) and adaptive control method based on the CARMA model are realized by using linear model to identify the target test system. However the real test system is very complicated because of various nonlinear factors. Linear models approximately describe the system only in a small range. Therefore, system simulation methods can not be used to validate the developed control algorithm and the uncertainty of test accordingly increases. As mentioned above, this paper presents a model to identify the nonlinear test system using NARMA dynamic neural network and discusses how to make the model parameters in detail. Using the test input-output series data, this network was trained by Levenberg-Marquardt method. Results of verification simulation show the validation of the nonlinear model.

In heavy truck driveline system, the components often include clutch, transmission, transfer case, drive shaft, etc. A fluid torque converter could be equipped in front of the transmission in order to improve the starting performance. Meanwhile, a hydraulic retarder could be introduced for auxiliary braking so as to adapt the truck to the brake on long downgrade in mountainous regions. Thus, the driveline heat load would have a notable increase. Both the fluid torque converter and the hydraulic retarder would produce a large quantity of heat, and a special cooling system is needed for adjusting the transmission fluid temperature with which the gains are potentially very large [1]. The heat load for driveline is often calculated based on empirical formula. For the heavy truck, however, if the heat value is underestimated, driveline components would suffer from overheated damage.