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With the increasingly serious global environmental and energy problems, as well as the increasing number of vehicles, pure electric vehicles with its advantages of environmental protection, low noise and renewable energy, become an effective way to alleviate environmental pollution and energy crisis. Due to the current pure electric vehicle power battery technology is not perfect, the range of pure electric vehicle has a great limit. Through the braking energy recovery, the energy can be reused, the energy utilization rate can be improved, and the battery life of pure electric vehicles can be improved. In this paper, a pure electric vehicle is taken as the analysis object, and the whole vehicle analysis model is built. Through the comparative analysis, based on the driver's braking intention and vehicle running state, the braking energy recovery control strategy of double fuzzy control is proposed.

Recreational vehicles have a lot of potential consumers in China, especially the type C recreational vehicle is popular among consumers due to its advantages, prompting an increase in the production and sales volumes. The type C vehicle usually has a higher air drag than the common commercial vehicles due to its unique appearance. It can be reduced by optimizing the structural parameters, thus the energy consumed by the vehicle can be decreased. The external flow field of a recreational vehicle is analyzed by establishing its computational fluid dynamic (CFD) model. The characteristic of the RV’s external flow field is identified based on the simulation result. The approximation models of the vehicle roof parameters and air drag and vehicle volume are established by the response surface method (RSM). The vehicle roof parameters are optimized by multi-objective particle swarm optimization (MO-PSO).

In the field of active safety, the active four-wheel-steering (4WS) system seems to be an attractive alternative and an effective tool to improve the vehicles' handling stability in lane-keeping control performance. Under normal using condition, the vehicle's lateral acceleration is comparatively small, and the mathematic relationship between the small side force excitation and the small slip angle of the tire is in the linear region. Furthermore, the effects of roll, heave, and pitch motions are neglected as well as the dynamic characteristics of the tires and suspension system in this work. Therefore, the linear quadratic control (LQC) theory is used to ensure that the output of the 4WS control system can keep track of the desired yaw rate and zero-sideslip-angle response can also be realized at the same time.

This paper presents a method of calculating temperature field of the piston by using a wavelet neural network (WNN) to identify the unknown boundary conditions. Because of the complexity of the heat transfer and limitations of experimental conditions of heat transfer analysis of the piston in a diesel engine, boundary conditions of the piston temperature field were usually obtained empirically, and thus the result itself was uncertain. By employing the capability of resolution analysis from a wavelet neural network, the method obtains improved boundary heat transfer coefficients with a limited number of measured temperatures. Using FEA software iteratively, results show the proposed wavelet neural network analysis method improves the prediction of unknown boundary conditions and temperature distribution consistent with the experimental data with an acceptable error.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.

Magnetorheological fluid (MRF) is used as the transmission medium of the hydraulic retarder. The rheological properties are regulated by changing the magnetic field to achieve accurate control of the retarder's braking torque. Under the action of the external magnetic field, the flow structure and performance of the MRF retarder will be changed in a short time. The apparent viscosity coefficient increases by several orders of magnitude, the fluidity deteriorates and the heat generated by the brake cannot be transferred through the liquid circulation, which will affect the braking torque of the retarder. Changing the surface area of the stator also has an influence on the braking torque of the retarder and the wall heat dissipation. In this study, the relationship between the braking torque of the MRF retarder and the stator surface area of the retarder was analyzed.

Driver distraction detection is crucial to driving safety when autonomous vehicles are co-piloted. Recognizing drivers’ behaviors that are highly related with distraction from real-time video stream is widely acknowledged as an effective approach mainly due to its non-intrusiveness. In recently years, deep learning neural networks have been adopted to by-pass the procedure of designing features artificially, which used to be the major downside of computer-vision based approaches. However, the detection accuracy and generalization ability is still not satisfying since most deep learning models extracts only spatial information contained in images. This research develops a driver distraction model based on a two-stream, spatial and temporal, convolutional neural network (CNN).

In order to avoid the braking recession on heavy commercial vehicles caused by the long-distance continuous braking of the main brake, the hydraulic retarder is widely used as an important brake auxiliary device in various heavy commercial vehicles to improve the vehicle safety. However, the hydraulic retarder not only has the advantages of large braking torque and good stability, but also has the disadvantages of poor retarding ability at low rotating speed, braking lag and difficulty in accurately controlling the braking torque. This paper introduces a new type of hydraulic retarder. The new retarder replaces the oil in the retarder with magnetorheological fluid and applies a magnetic field in the retarder arrangement space, so that slows down the vehicle by using the rheological properties of the magnetorheological fluid under the magnetic field.

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.

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.

People, vehicles and circumstances are the three key factors, which affect transportation systems. Offering more information to the driver and helping him observe on all sides so that he can make decisions correctly are of great importance for reducing accidents. According to the present traffic regulations, in this paper we focus on the rules and process used during steering and proposed to implement them in a car information central control system based on CAN. A comparison of the brake time between brake by driver and by radars revealed the great interest of using ECUs connected by CAN network.

The mountainous roads are rugged and complex, so that the driver can not make accurate judgments on dangerous road conditions. In addition, most heavy vehicles have characteristics of large weight and high center of gravity. The two factors above have caused most of the car accidents in mountain areas. A research shows that 90% of car accidents can be avoided if drivers can respond within 2-3 seconds before the accidents happen. This paper proposes a speed warning scheme for heavy-duty vehicle over the horizon in mountainous area, which can give the drivers enough time to respond to the danger. In the early warning aspect, this system combines the front road information, the vehicle characteristics and real-time information obtained from the vehicle, calculates and forecasts the danger that may happen over the horizon ahead of time, and prompts the driver to control the vehicle speed.

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.

With the continuous increasing requirements of commercial vehicle weight and speed on highway transportation, conventional friction brake is difficult to meet the braking performance. To ensure the driving safety of the vehicle in the hilly region, the eddy current retarder (ECR) has been widely used due to its fast response, lower prices and convenient installation. ECR brakes the vehicle through the electromagnetic force generated by the current, and converted vehicle mechanical energy into heat through magnetic field. Air cooling structure is often used in the traditional ECR and cooling performance is limited, which causes low braking torque, thermal recession, and low reliability and so on. The water jacket has been equipped outside the eddy current region in this study, and the electric ECR is cooled through the water circulating in the circuit, which prolongs its working time.

The hydraulic retarder is an auxiliary braking device used for commercial vehicle in a long slope brake, and its transmission oil generates a lot of heat in its working process. If the heat of transmission doesn’t go through a reasonable management, it will seriously affect the braking performance of hydraulic retarder. To cool down the transmission oil, it will aggravates the load of the engine cooling system, and the long cooling path sometimes causes heat exchange not timely. When the Rankine cycle is used for cooling the hydraulic retarder transmission oil in virtue of its good heat transfer performance in phase change process, it can make the transmission oil temperature controlled more stable. In this new system, the setting parameters of the Evaporate-condensate system will affect the stability of the transmission oil temperature in the hydraulic retarder inlet and the energy recovery efficiency of the system.

This research is based on the Controller Area Network (CAN) bus, and briefly analyzed its communication protocol with reference to the layered model of Open System Interconnect Reference Model (OSI). Subsequently, a data acquisition system was designed and developed including a Vehicle Communication Interface (VCI) and a laptop. After the overall architecture was built, the communication mechanism of the VCI was studied. Furthermore, the lap top app was built using the layered design followed by the implementation of a scheme for data collection and experimentation involving the test driving of a real car on road. Finally, the driving style was identified by means of fuzzy reasoning and solving ambiguity based on fuzzy theory; via training the acceleration sample and forecast using the excellent learning and generalization ability of Support Vector Machine (SVM) for high-dimensional, finite samples.

Whether the available energy of the on-board battery pack is enough for the driver’s next trip is a major contributor in slowing the growth rate of Electric Vehicles (EVs). What’s more, the actual capacity of the battery pack depend on so many factors that a real-time estimation of the state of charge of the battery pack is often difficult. We proposed a big-data based algorithm to build a battery pack dynamic model for the online state of charge estimation and a stochastic model for the energy consumption prediction. And the good performance of sensors, high-bandwidth communication systems and cloud servers make it convenient to measure and collect the related data, which are grouped into three categories: standard, historical and real-time data. First a resistance-capacitance ( RC )-equivalent circuit is taken consideration to simplify the battery dynamics.

Using friction brakes for long time can increase easily its temperature and lower vehicle brake performance in the downhill process. The drivers' hysteretic perception to future driving condition could mislead them to stop untimely the engine brake, and some other auxiliary braking devices are designed to increase the brake power for reduction of the friction brake torque. The decompression engine brake has complex structure and high cost, and the application of eddy current retarder or hydraulic retarder on the commercial vehicles is mainly limited to their cost and mass. In this paper, an innovative brake guidance system for commercial vehicles with coordinated friction brakes and engine brake is introduced to guide the drivers to minimize the use of the friction brakes on the downhill with consideration of future driving conditions, which is aimed at releasing the engine brake potential fully and controlling the friction brake temperature in safe range.

Head-up Display (HUD) system can avoid drivers’ distraction on dashboard and effectively reduce collisions caused by emergency events, which is gradually being realized by researchers around the world. However, the current HUD only displays information like speed, fuel consumption, other information like acceleration and braking can’t be displayed yet. This research will use the indicator symbol‘s color and position change to remind drivers to brake or accelerate. Drivers can do driving operation timely and accurately. The system has the advantages of safety, intuition and real-time. The vehicle safe speed is calculated according to the road parameters, like adhesion coefficient and slope, and vehicle parameters, such as vehicle mass and centroid. Then, the appropriate braking operations are obtained by combining the vehicle driving state. The braking information is corresponded to the color and position change of the indicator symbol to prompt the drivers by the HUD interface.

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.