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Overloading of trucks can easily cause damage to roads, bridges and other transportation facilities, and accelerate the fatigue loss of the vehicles themselves, and accidents are prone to occur under overload conditions. In recent years, various countries have formulated a series of management methods and governance measures for truck overloading. However, the detection method for overload behavior is not efficient and accurate enough. At present, the method of dynamic load identification is not perfect. No matter whether it is the dynamic weight measurement method of reconstructing the road surface or the non-contact dynamic weight measurement method, little attention is paid to the difference of different vehicles. Especially for different vehicles, there should be different load limits, and the current devices are not smart enough.

The vehicle overload seriously jeopardizes traffic safety and affects traffic efficiency. At present, the static weighing station and weigh-in-motion station are both relatively fixed, so the detection efficiency is not high and the traffic efficiency is affected; the on-board dynamic weighing equipment is difficult to be popularized because of the problem of being deliberately damaged or not accepted by the purchaser. This paper proposes an efficient, accurate, non-contact vehicle overload identification method which can keep the road unimpeded. The method can detect the vehicle overload by the relative distance (as the characteristic distance) between the dynamic vehicle's marking line and the road surface. First, the dynamics model of the vehicle suspension is set up. Then, the dynamic characteristic distance of the traffic vehicle is detected from the image acquired by the calibrated camera based on computer vision and image recognition technology.

The high gravity center of the concrete mixer truck reduces the truck’s stability while steering. The rolling stirring tank makes the stability even worse than the regular engineering vehicle due to the dynamic variation of the centroid position. Most of the researches on the rollover stability of concrete mixer trucks focus on the rollover model establishment and dynamic simulation module. The change of concrete centroid is ignored when the safety cornering speed is calculated. This paper proposes a pre-warning method for the cornering speed of concrete mixer trucks based on centroid dynamic simulation. In the method, the mixing tank stirring model and the vehicle driving dynamic model are established on the Fluent and TruckSim simulation platforms, respectively. The theoretical speed threshold obtained by simulation is used as the evaluation index of the warning speed in the curve. Firstly, the dynamic simulation of the stirring tank model is carried out by Fluent.

The hydraulic retarder is the most stabilized auxiliary braking system [1-2] of heavy-duty vehicles. When the hydraulic retarder is working during auxiliary braking, all of the braking energy is transferred into the thermal energy of the transmission medium of the working wheel. Theoretically, the residual heat-sinking capability of the engine could be used to cool down the transmission medium of the hydraulic retarder, in order to ensure the proper functioning of the hydraulic retarder. Never the less, the hydraulic retarder is always placed at the tailing head of the gearbox, far from the engine, long cooling circuits, which increases the risky leakage risk of the transmission medium. What's more, the development trend of heavy load and high speed vehicle directs the significant increase in the thermal load of the hydraulic retarder, which even higher than the engine power.

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.

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.

The hydraulic retarder used in commercial vehicles can provide hydraulic damping to generate braking torque, reducing the pressure of the braking system on the slope section and increasing the safety. In this paper, the magnetorheological fluid with fast magnetic field reflection characteristics is used to increase the response speed of the hydraulic retarder, which can effectively reduce the response time of the hydraulic retarder. In this paper, the influence of the change of circumferential magnetic field on the braking torque of the magnetorheological fluid retarder is studied.

Vehicle hydraulic retarders are applied in heavy-duty trucks and buses as an auxiliary braking device. In traditional cooling systems of hydraulic retarders, the working fluid is introduced into the heat exchanger to transfer heat to the cooling liquid in circulation, whose heat is then dissipated by the engine cooling system. This prevents the waste heat of the working fluid from being used effectively. In hydraulic retarder cooling system based on the Organic Rankine Cycle, the organic working fluid first transfers heat with the hydraulic retarder working fluid in Rankine cycle, and then outputs power through expansion machine. It can both reduce heat load of the engine cooling system, and enhance thermal stability of the hydraulic retarder while recovering and utilizing braking energy. First of all, according to the target vehicle model, hydraulic retarder cooling system model based on Rankine cycle is established.

In the Rankine cycle, the pressure differential generated by the phase change of the working fluid produces turbine output power, which enables the recovery of waste heat from the internal combustion engine. The heat transfer ability of the evaporator is the key factor that determines the quality of turbine's mechanical work. In this paper, the performance of the evaporator with two-phase zone and preheated zone is studied. After obtaining the thermal characteristics of diesel engine exhaust from the experimental data, the mathematical model of the evaporator is built according to the specific working conditions of ORC and geometrical parameters of the evaporator. Three typical engine operating conditions are used to estimate the heat transfer characteristics of the evaporator. The result shows that, in the evaporator, the heat transfer coefficient of the Rankine working fluid is much greater than the exhaust side of the engine.

The hydraulic retarder is an important auxiliary braking device. With merits such as its high braking torque, smooth braking, low noise, long service life and small size, it is widely used on modern commercial vehicles. Transmission fluid of traditional hydraulic retarder is cooled by engine cooling system, which exhausts the heat directly and need additional energy consumption for the thermal management component. On account of the working characteristics of hydraulic retarder, this study designs a set of waste heat recovery system based on the Organic Rankine Cycle (ORC). Under the premise of ensuring stable performance of hydraulic retarder, waste heat energy in transmission fluid is recycled to supplement energy requirements for cooling system. First of all, a principle model, which is scaled down according to D300 retarder`s thermal power generation ration of 1:100, is established. Then through theoretical calculations, components' structural parameters of the ORC are determined.

As a key component of airstream system equipped in the road sweeper, the structure of the suction nozzle determines its internal flow field distribution, which affects the dust-sucking efficiency to a great degree. This research is aiming to determine a better suction nozzle structure. Starting with an analysis of the one used in a certain type of road sweeper, the initial model of the suction nozzle is established, and the internal flow field is simulated with typical computational fluid dynamics (CFD) software named FLUENT. Based on the simulation results, the dust-sucking capability of the initial structure is evaluated from the aspects of pressure and velocity distribution. Furthermore, in order to explore the influence of different structural parameters on the flow field distribution within the suction nozzle, models with different cavity heights and shoulder angles are established, and Univariate Method is utilized to analyze the contrast models.

To improve the braking energy recovery rate of pure electric garbage removal vehicles and ensure the braking effect of garbage removal vehicles, a strategy using particle swarm algorithm to optimize the regenerative braking fuzzy control of garbage removal vehicles is proposed. A multi-section front and rear wheel braking force distribution curve is designed considering the braking effect and braking energy recovery. A hierarchical regenerative braking fuzzy control strategy is established based on the braking force and braking intensity required by the vehicle. The first layer is based on the braking force required by the vehicle, based on the front and rear axle braking force distribution plan, and uses fuzzy controllers.

Semi-active suspension has been widely applied in commercial vehicle suspension in order to get good riding comfortableness. Fuzzy logic control (FLC) has been widely applied in the field of kinetic control because control rule of FLC is easy to understand. But the gain of fuzzy rules and adjustment of membership functions usually depend on experts' experiences and repeated experiments, thus the fuzzy rules and membership functions has strong subjectivity, also are easily affected by environment of experiments, so the main problem of fuzzy logic controller design is selection and optimization of fuzzy rules and membership functions. Genetic Algorithms (GA) is the algorithm that searches the optimal solution through simulating natural evolutionary process and is one of the evolution algorithms which have most extensive impact.

How to improve the measurement accuracy of road gradient is the key content of the research on the speed warning of commercial vehicles in mountainous roads. The large error of the measurement causes a significant effect of the vehicle speed threshold, which causes a risk to the vehicle's safety. Conventional measuring instruments such as accelerometers and gyroscopes generally have noise fluctuation interference or time accumulation error, resulting in large measurement errors. To solve this problem, the Kalman filter method is used to reduce the interference of unwanted signals, thereby improving the accuracy of the slope measurement. However, the Kalman filtering method is limited by the estimation error of various parameters, and the filtering effect is difficult to meet the project research requirements.

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.

The lightweight design of a vehicle can save manufacturing costs and reduce greenhouse gas emissions. For the off-road vehicle and truck, the chassis frame is the most important load-bearing assembly of the separate frame construction vehicle. The frame is one of the most assemblies with great potential to be lightweight optimized. However, most of the vehicle components are mounted on the frame, such as the engine, transmission, suspension, steering system, radiator, and vehicle body. Therefore, boundaries and constraints should be taken into consideration during the optimal process. The finite element (FE) model is widely used to simulate and assess the frame performance. The performance of the frame is determined by the design parameters. As one of the largest components of the vehicle, it has a lot of parameters. To improve the optimum efficiency, sensitivity analysis is used to narrow the range of the variables.

Dynamic and economic performance play an important role in the vehicle evaluation indexes, and also are crucial parts considered during the design progress. This paper applies a method of parameters matching of powertrain to one Pure Electric City Bus(PECB), with which a four-speed transmission dynamic system is designed. Meanwhile two powertrain models adopting motors with identical peak power but different base speeds and peak torques coupled with two-speed transmission or without transmission are introduced for comparison to analyze if a smaller motor performs better in performance. The three models are based on identical type of bus. Then according to the powertrain parameters, simulation models of three bus models are established respectively. From the results of simulation, vehicle performances of the four-speed transmission powertrain, especially economic performance, are compared with the other two.

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.

When dump trucks unload dusty materials, dust particles with a diameter of 1 to 75 microns slide out of the dump body and float into the air. Dust particles naturally settle down spending a few hours, which causes air pollution. People who work in this environment daily suffer serious physical harm. To study the movement of dust particles during the unloading process, a scaled-down model is used to simulate the process of dump truck unloading gravel, and a high frame rate camera is used to record the movement trajectory of dust particles during the unloading process. In this paper, by observing the movement process of unloading dust particles by dump trucks, based on the principle of dynamics, a mathematical model describing the unloading of dust particles in the dump body and a mathematical model of the diffusion of dust particles in the air are established. Take the small gravel sampled at the construction site as an example of the experiment.

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.