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According to the resonant pavement crusher's work principle, its front frame mounted with the resonance system must meet the needs of the structural requirements. To satisfy the strength and stiffness requirement and avoid the resonance, the natural frequency of the front frame should be designed away from the crusher's working frequency. In this paper, the author builds a finite element model of the front frame and analyses its modal. According to the modal analysis results, the fourth modal frequency is close to the working frequency of the crusher. So the front frame should be optimized. In the finite element model, the front frame has been divided into a number of components of shell elements. Through optimal Latin hypercube experimental design, the author analyses the different component thickness's relationship of the frequencies of the front frame. The components with higher correlation coefficient have been chosen as the variables of optimization.

The automobile exhaust energy can be recovered by the thermoelectric module generator(TEG). Owing to the complex urban traffic, the exhaust gas’s temperature fluctuations are resulted, which means the unstable hot-end temperature of the TEG. By installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, it is possible to appropriately reduce the temperature fluctuation, but there is still a fluctuation of the TEG’s power output. Then by adding voltage filter circuit (VFC) after the TEG, the power output stability can be improved. This research uses SHCM and VFC to improve the stability of the exhaust gas generation. Firstly, the three-dimensional heat transfer model of the exhaust pipe thermoelectric power generation system is established. The heat capacity materials with low thermal resistance and high heat capacity were selected as the research object based on previous research.

The Organic Rankine Cycle System is an effective approach for recovering the engine exhaust thermal energy. The physical characteristic of the Rankine fluid is the key factor for the capacity and the stability of the expander power output. In the research, the influences of the evaporator organic medium state and flow rate on the expander power output are fully analyzed for the sufficient utilization of the waste thermal energy. Firstly, the exhaust characteristics of the diesel engine were processed by the data of the bench test. Then, the integral mathematical model of the Organic Rankine Cycle was built. Based on the comparison for the 2-zone and 3-zone evaporator, the influence for expander output are analyzed especially emphasis on the factors of engine working condition, the flow rate, temperature and state of Rankine fluid.

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 hydraulic retarder is an auxiliary braking device generally equipped on commercial vehicles. Its oil temperature change influences the brake performance of hydraulic retarder. The Organic Rankine Cycle (ORC) is a good means to recover exhausted heat. Moreover, it can cool oil and stably control oil temperature with the help of heat absorption related with evaporation. Comprehensively considering the heat-producing characteristics of hydraulic retarder and the temperature control demand, the aimed boundary conditions are determined. Also the changing rules about the working medium flow rate are obtained. In this work, the heat-producing properties of hydraulic retarder under different conditions and the oil external circulating performance is firstly analyzed. By researching the system’s adaptation to the limiting conditions, the aimed temperature to control is prescribed.

With the improvement of occupants’ awareness on the driving safety, hydraulic retarder applications increase quickly. The traditional hydraulic retarder, on the one hand, exhausts the waste heat of transmission oil by the engine cooling system; on the other hand, the engine power should be consumed to drive the water pump and the engine cooling fan for maintaining the normal operation of the auxiliary braking system. In this study, the Organic Rankine Cycle (ORC) instead of the traditional hydraulic retarder water-cooling system is applied to achieve the effective temperature control of the hydraulic retarder, while the waste heat of transmission oil could be recovered for saving vehicle energy consumption. The ORC fluid selection needs comprehensive consideration for the net power of the ORC and the optimal temperature range of the retarder transmission oil at both the inlet and outlet end, which is the key issue to ensure the stability and efficiency of the ORC system performance.

While the car ownership increasing all over the world, the unutilized thermal energy in automobile exhaust system is gradually being realized and valued by researchers around the world for better driving energy efficiency. For the unexpected urban traffic, the frequent start and stop processes as well as the acceleration and deceleration lead to the temperature fluctuation of the exhaust gas, which means the unstable hot-end temperature of the thermoelectric module generator (TEG). By arranging the heat conduction oil circulation at the hot end, the hot-end temperature’s fluctuation of the TEG can be effectively reduced, at the expense of larger system size and additional energy supply for the circulation. This research improves the TEG hot-end temperature stability by installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, which has the merits of simple structure, none energy consumption and light weight.

Vehicle exhaust waste-heat recovery with thermoelectric power generators can improve energy efficiency, as well as vehicle fuel economy. In the conventional structure, the hot-end of thermoelectric module is directly connected with the outer wall of the exhaust pipe, while the cold-end is connected with the water pipe’s outer wall of the vehicle engine cooling cycle. However, the variety of vehicle engine operating conditions leads to the instability of the hot-end temperature, which will reduce the generating efficiency of the thermoelectric modules and also shorten its service life. This research is on the basis of constructing a heat transfer oil circulation, and to study the action principles and implementation methods of it.

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.

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.