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With the shortage of energy and the continuous development of automotive technology, electric vehicles are gradually gaining popularity. The energy of electric vehicles mainly comes from the power grid, and its large-scale use is inseparable from the support of the power system. However, electric vehicles consume power quickly, have short driving ranges, and frequently charge, and there are plenty of problems such as disorder and randomness in charging, which is not conducive to rational planning of the power grid. Optimizing the charging problem of electric vehicles can not only save power resources but also bring huge economic benefits to operators of charging stations. In this paper, the CAN bus communication protocol, combined with GPS positioning, LabVIEW monitoring, GPRS transmitting and other technical means, can realize the information exchange of the "vehicle-charging device-distribution network".

At present, many electric vehicles are often equipped with only a single-stage final drive. Although the single-stage speed ratio can meet the general driving requirements of electric vehicles, if the requirements of the maximum speed and the requirements for starting acceleration or climbing are met at the same time, the power demand of the drive motor is relatively large, and the efficient area of the drive motor may be far away from the operating area corresponding to daily driving. If the two-speed automatic transmission is adopted, the vehicle can meet the requirements of maximum speed, starting acceleration and climbing at the same time, reduce the power demand of the driving motor, and improve the economy under certain power performance. This is especially important for medium and large vehicles.

In the intelligent speed planning system, real-time estimation of road slope is the key to calculate slope resistance and realize the vehicles’ active safety control. However, if the road slope is measured by the sensor while the commercial vehicle is driving, the vibration of the vehicle body will affect its measurement accuracy. Therefore, the relevant algorithm is used to estimate the real-time slope of the road when the commercial vehicle is driving. At present, many domestic and foreign scholars have analyzed and tested the estimation of road slope by the least square method or Kalman filter algorithm. Although the two methods both can achieve the estimation, the real-time performance and accuracy still need to be improved. In this paper, for traditional fuel commercial vehicle, the Kalman filter algorithm based on the kinematics and the extended Kalman filter algorithm based on the longitudinal dynamics are respectively used to estimate the road slope.

The thermal management system is essential for the safe and long-term operation of the power battery. The temperature difference between the individual cells exceeds the acceleration of the battery performance, which leads to battery out of use and affects the performance of the vehicle. Compared with the low heat transfer coefficient of the air-cooling system, the complex structure of the liquid-cooling system and the large quality of phase change material system, the heat pipe has high thermal conductivity, strong isothermal performance and light weight, it’s an efficient cooling element that can be used for thermal management. In this study, the flat plate heat pipe(FPHP) is used to manage the temperature of the battery, through experiments, the optimized placement of the flat heat pipe is obtained.

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.

The objective of this study was to assess the effect of different driving speeds on autonomic nervous activities in healthy drivers on highway by using power spectral analysis of heart rate variability (HRV). A total of 30 healthy male drivers were randomly divided into three groups: A (with speed of 40 km/h), B (with speed of 80 km/h) and C (with speed of 120 km/h). All drivers were required to be well rested before the experiments. All subjects of three groups were required to drive the car on A20 highway for 2 hours. Heart rate signals were collected throughout the experiment and blood pressure was measured and compared before and after the experiment. Subjective evaluation to a questionnaire was obtained after the driving task in three groups. After the driving task, low frequency (LF) component, high frequency (HF) component and their ratio LF/HF of HRV in normalized units (NU) were calculated and compared between both groups and between the beginning and the end of the task.

The objective of this study was to assess the effects of magnetic acupuncture applied to Dazhui (DU14) and Neiguan (PC6) points on drivers' autonomic nervous activities by power spectral analysis of heart rate variability (HRV) during long-term driving on a highway at the speed of 80 km/h. 20 healthy male drivers were randomly divided into two groups: A (study group) and B (control group). All drivers were required to be well rested before the experiment s. All subjects of both groups were required to drive the car on A20-highway for 4 hours. During the driving, magnetic acupuncture were applied to the DU14 and PC6 points for group A while the subjects drove the car for 3.5 hours, and for group B magnetic acupuncture were applied to non-acupuncture points which were 1.5 cm away from the two acupuncture points respectively over the same time. Subjective evaluation to a questionnaire was obtained after the driving task in two groups.

The remarkable evolution of steel technology in recent years has resulted in the development of new High Strength Steels (HSS) that are increasingly used in today's automobiles. The advanced performance of these grades in ductility and rapid hardening characteristics provides an opportunity to stamp complex geometries with in-panel material strengths far exceeding those of conventional high strength grades of steel. This provides an opportunity to improve an automotive body's performance in crash, durability and strength while reducing the overall weight of the vehicle. An improved understanding of the forming characteristics of these advanced HSS and accurate prediction of the material processing strain will allow vehicle designers to fully explore the opportunities of increased yield, strain hardening, formability and strength and the potential this creates to reduce mass and improve the performance of the automotive body.

The purpose of this study was to quantifiably evaluate driver mental fatigue using the power spectral analysis of the heart rate variability (HRV). The quantitative detector of driver fatigue can present appropriate warnings and help to prevent traffic accidents. A simulation creating driver mental workload was set up using vigilance, considered to be an accurate assessment of driver mental workload, to evaluate a driver's performance. In the experiment eight healthy male subjects were required to perform a vigilance task for 90 minutes. The physiological variables for evaluating driver mental load were spectral values of heart rate variability (HRV). As a result HRV showed a high correlation with driver mental fatigue.

In designing an automobile seat, it is important to minimize the fatigue experienced by the driver resulting from long-term sitting. In this study eight healthy male subjects participated in two group experiments that were A-group and B-group. Acupoints combined with magnetism stimuli were put on to the subjects for reducing postural fatigue in B-group during the simulated driving. The surface electromyography (sEMG) of muscle activity at L4/L5 as well as subjective self-reporting on fatigue were recorded and tested. Analyzing and comparing the EMG median frequency and the subjective evaluations between two groups a conclusion that acupoints combined with magnetism stimuli could reduce the driver postural fatigue was drawn.

A 2001 SAE paper et al. [1,2] compared the formability aspects of six different grades of galvanealed steel [IF (270E), C-Mn (440W-1), low C - high Mn (440W-2), HSLA440 (440R), HSLA590 (590R) and DP590 (590Y)]. This study has been expanded to evaluate five additional advanced galvanealed steel grades [Low yield type DP780 (780YL), High yield type DP780 (780YM), DP980 (980Y), TRIP590 (590T), and TRIP780 (780T)]. The study presents material properties, forming characteristics in several lab tests and spring back characteristics. The study provides the actual and relative performance of these eleven steels and conclusions on the advantages these grades provide in cost-effective and mass-effective solutions to the manufacturing and performance requirements of the automotive body.

The closed cabin temperature is anticipated to be cooled down when it is a bit hot inside the driving car. The traditional air-condition lowers the cabin temperature by frequently switching the status of the compressor, which increases the engine’s parasitic power and shortens the compressor’s service-life. The semiconductor auxiliary cooling system with the properties of no moving parts, high control precision and quick response has the potential to assist the on-board air-condition in modulating the cabin temperature with relative small ranges. Little temperature differences between the cabin and the outside environment means that the system energy consumption to ensure the occupant comfort is relatively low and the inefficiency could be made up by the renewable energy source.

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.

Typical vehicle speed deceleration occurs at the freeway exit due to the driving direction change. Well conducting the driver to control the velocity could enhance the vehicle maneuverability and give drivers more response time when running into potential dangerous conditions. The freeway exit speed limit sign (ESLS) is an effect way to remind the driver to slow down the vehicle. The ESLS visibility is significant to guarantee the driving safety. This research focuses on the color variable ESLS system, which is placed at the same location with the traditional speed limit sign. With this system, the driver could receive the updated speed limit recommendation in advance and without distraction produced by eyes contract change over the dashboard and the front sight. First, the mathematical model of the drivetrain and the engine brake is built for typical motor vehicles. The vehicle braking characteristics with various initial speeds in the deceleration area are studied.

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.

Road traffic congestion sometimes happens at tunnel exit even without high traffic flow. One reason is that the deceleration process is imperceptible when the vehicle is driving to the tunnel exit with gradual upgrade slopes. Nowadays regulations are more concentrated in transport sectors, and control measures are applied to vehicles through the tunnel. This process is careless of vehicles’ specific characteristics and easily distract the driver attention. In this paper, a tunnel climbing acceleration reminder system is introduced. When the speed drop is detected and the analysis show this is due to the driver's unconscious behavior, the system will remind the driver to speed up. Based on the dynamic model and the tunnel properties, the relationship between the throttle opening degrees and the duration with the speed change is studied. Then, the engine braking is considered for the variation of speeds and slopes.

Automotive Front Lighting System(AFS) can receive the steering signal and the vehicular speed signal to adjust the position of headlamps automatically. AFS will provide drivers more information of front road to protect drivers safe when driving at night. AFS works when there is a steering signal input. However, drivers often need the front road's information before they turn the steering wheel when vehicles are going to go through a sharp corner, AFS will not work in such a situation. This paper studied how to optimize the working time of AFS based on GIS (Geographic Information System) and GPS(Geographic Information System) to solve the problem. This paper analyzed the process of the vehicle is about to go through a corner. Low beams and high beams were discussed respectively.

The drivers' hysteretic perception to surrounding environment will affect vehicular fuel economy, especially for the heavy-duty vehicles driving under complex conditions and long distance in mountainous areas. Unreasonable acceleration or deceleration on the slope will increase the fuel consumption. Improving the performance of the engine and the transmission system has limited energy saving potential, and most fuel-efficient driving assistant systems don't consider the road conditions. The main purpose of this research is to introduce an economic driving scheme with consideration of the prestored slope information in which the vehicle speed in mountainous slopes is reasonably planned to guide the driver's behavior for reduction of the fuel consumption. Economic driving optimization algorithm with low space dimension and fast computation speed is established to plan accurate and real-time economic driving scheme.

The heavy-duty vehicles have large transportation capacity. Gross mass and center of gravity position of the heavy-duty vehicles vary with the cargo mass and the driving condition, which affect driving safety and handling stability. Gross mass and center of gravity position of the vehicles are usually measured on fixed test platform, and the vehicles are stationary or pass the platform slowly in the measurement process. Most dynamic weighing system could not measure the center of gravity position of the vehicles. On-board mass and center of gravity of motor vehicles measurement system mainly based on the tire pressure information could measure gross mass and center of gravity position accurately in the driving process. The measurement errors of the sensors are effectively decreased by filtering collected sensor data. The relationship between the tire pressure and the tire load is built when the vehicle is stationary.

Path planning system, which is one of driver assistance systems, can calculate the driving paths and estimate the driving time through the road information provided by information source. Traditional path planning systems calculate the driving paths through Dijsktra's algorithm or A* algorithm but only consider the road information from electronic maps. It is not safe enough for operating vehicles because of the insufficient information of vehicle performance as well as the driver's willingness. This study is based on the Dijsktra's algorithm, which comprehensively considered vehicular active safety constraints such as road information, vehicle performance and the driver's willingness to optimize the Dijsktra's algorithm. Then the path planning system can calculate the optimal driving paths that would satisfy the safety requirement of the vehicle. This study used LabVIEW as a visual host computer and MATLAB to calculate dynamic property of the vehicle.