Search Results

In the process of truck overload and over-limit detection, it is necessary to detect the characteristics of the vehicle's size, type, and wheel number. In addition, in some vehicle vision-based load recognition systems, the vehicle load can be calculated by detecting the vibration frequency of specific parts of the vehicle or the change in the length of the suspension during the vehicle's forward process. Therefore, it is essential to quickly and accurately identify vehicle features through the camera. This paper proposes a vehicle feature recognition method based on image semantic segmentation and Python, which can identify the length, height, number of wheels and vibration frequency at specific parts of the vehicle based on the vehicle driving video captured by the roadside camera.

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.

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.

It’s not easy to start the engine in winter, especially in frigid highlands, because the low temperature increases the fuel’s viscosity, decreasing the lubricating oil flow ability and the storage performance of battery. Current electrical heating method can improve the engine starting performance in low temperature condition, but this method adds an external power to the engine, leading to the engine cannot maintain an efficient energy utilization. A warming device using the solar energy is designed to conserve the energy during the daytime, and directly warm up the engine at the time when the engine turns off for a long time, especially during the night. A solar collector installed on the top of the vehicle is used to convert the solar energy to the thermal energy, which is then transferred to the heat accumulator that contain the phase-change medium which can increase the heat storage performance.

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.

Li-ion power battery is the core component of the electric vehicle power system, and the battery temperature will increase because of the electrochemical reaction of the Li-ion battery. The heat accumulates inside of the battery, which can degrade the working performance of the power battery and shorten the battery cycle life. At present, the wind cooling technology is relatively mature. However, it cannot achieve ideal heat dissipation effect under the working conditions of the high-power or high ambient temperature. In this research, the battery thermal management is carried out by the characteristics of the working fluid’s flowing phase change heat transfer. The phase change working fluid is R-1233zd(E) which is a kind of environmentally friendly liquid with nonconductive and nonflammable. It can achieve the purpose of controlling the battery’s temperature using the characteristics of isothermal heat absorption under different gas phase rate of phase change working fluid.

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.

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.

There are a large number of curves and slopes in the mountainous areas. Unreasonable acceleration and deceleration in these areas will increase the burden of the brake system and the fuel consumption of the vehicle. The main purpose of this paper is to introduce a speed planning and promotion system for commercial vehicles in mountainous areas. The wind, slope, curve, engine brake, and rolling resistances are analyzed to establish the thermal model of the brake system. Based on the thermal model, the safe speed of the brake system is acquired. The maximum safe speed on the turning section is generated by the vehicle dynamic model. And the economic speed is calculated according to the fuel consumption model. The planning speed is provided based on these models. This system can guide the driver to handle the vehicle speed more reasonably.

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.

The Organic Rankine Cycle System (ORC) is an effective means to use the solar energy. The system adopts the solar energy on the car roof as the heat source to make the ORC work and drive the thermoelectric air-conditioner. It can improve the entering comfort on the parking condition and the vehicle energy utilization efficiency. In this research, the system comprehensively applied the principle of sunshine concentration, heat collection and photo electricity. Then considering the working condition and performance features of ORC system, the car roof was designed to have a compact structure, through which the efficiency of the solar vehicle system could be improved. Firstly, the research analyzed the heat source temperature and the heat flux impact on the output power of the ORC system. After that, the performance of heat collection was identified according to the given thermoelectric air-condition’s power requirements.

As an important input parameter of intelligent vehicle active safety technology, road adhesion coefficient is of great significance in autonomous collision avoidance, emergency braking and collision avoidance, and variable adhesion road motion control. Traditional recognition methods based on vehicle dynamics require large data volume and low solution accuracy. This paper proposes an adhesion coefficient recognition method based on Elman neural network and Kalman filter. By establishing a seven-degree-of-freedom vehicle dynamics model, dynamic parameters such as yaw angular velocity, longitudinal velocity, lateral velocity, and angular velocity of each wheel, which are easy to measure and strongly related to the road adhesion coefficient, are analyzed as the input of the neural network model.

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.

The sweeping vehicle has made a great contribution to the cleaning of urban roads. The traditional electric sweeping vehicle uses the main and auxiliary motors to drive the driving system and the operating system respectively. However, because the sweeper is in a low-speed working condition for a long time, and the drive motor must meet the demand for high power, there exist problems of low motor utilization and high cost. Aiming at this phenomenon, a dual-motor power coupling system based on planetary gears is proposed. First, analyze the driving mode of the dual-motor coupling power system according to the actual working scheme of the sweeper, and match the parameters of the motor based on this. Second, on the premise of meeting the power requirements, analyze and divide the working range of each drive mode based on the principle of minimum energy consumption, and then obtain the best drive mode switching control and speed and torque distribution strategy.

In winter, the temperature of the coldest month is below -20°C. Low temperature makes it difficult to start a diesel engine, combust sufficiently, which increases fuel consumption and pollutes the environment. The use of an electric power-driven auxiliary heating system increases the battery load and power consumption. Solar thermal energy has the advantages of easy access, clean and pollution-free. The coolant in the cylinder block of the diesel engine has a large contact area within the cylinder and is evenly distributed, which can be used as a heat transfer medium for the warm-up. A one-dimensional heat transfer model of the diesel engine block for the coolant warm-up is developed, and the total heat required for the warm-up is calculated by an iterative method in combination with the warm-up target.

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.

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.

With the development of highway transportation and automobile industry technology, highway truck overload phenomenon occurs frequently, which poses a danger to road safety and personnel life safety. So it is very important to identify the overload phenomenon. Traditionally, static detection is adopted for overload identification, which has low efficiency. Aiming at this phenomenon, a dynamic overload identification method is proposed. Firstly, the coupled road excitation model of vehicle speed and speed bump is established, and then the 4-DOF vehicle model of half car is established. At the same time, considering that the double input vibration of the front and rear wheels will be coupled when vehicle passes through the speed bump, the model is decoupled. Then, the vertical trajectory of the body in the front axle position is obtained by Carsim software simulation.

As one of the core components of electric vehicle, the performance of power battery is largely determined by thermal management system. Air cooling is difficult to meet the heat dissipation requirements of high-power power batteries. Liquid cooling arrangement is complex and requires high sealing performance. Phase change materials will increase the mass of battery packs. Heat pipes have good heat conduction, temperature equalization performance and light weight, and it is an ideal cooling and heat dissipation technology with efficient cooling fins. In this paper, a thermal management system of power battery based on heat pipe and fin is proposed. The maximum temperature and wall temperature difference of power battery are reduced by heat pipe and fin heat dissipation. The influence of different fin spacing and heights on the thermal management system is studied, and then the fin spacing and height are optimized.

The sweeper vehicle plays a very key role in maintaining the urban environment. If the sweeper vehicle can accurately and efficiently identify and classify the ground garbage in the working process, it can greatly improve the working efficiency of the sweeper vehicle and reduce the consumption of manpower. Although the deep learning algorithm based on DUC and PSPNet has high accuracy, the recognition speed is low. ENet is a lightweight network, which greatly improves efficiency, but significantly sacrifices accuracy. This paper presents an improved real-time detection lightweight network based on PSPNet, which takes into account the operation speed and accuracy. The network takes PSPNet as the backbone network, and increases the stride in the convolution process, to reduce the size of the feature map and reduce the amount of calculation.