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In the racing world, speed is everything, and the Formula Student cars are no different. As one of the key means to improve the speed of the car, lightweight plays an important role in the racing world. The weight reduction of unsprung metal parts can not only improve the driving speed, but also effectively optimize the dynamic of the car, so the lightweight design of unsprung parts has attracted much attention. In the traditional Formula Student racing car, the hub and spoke are two independent parts, they are fixed by four hub bolts or a central locking nut, the material of these fasteners is usually steel, so it brings a lot of weight burden. In order to achieve unsprung lightweight, a new type of wheel part design of Formula Student racing car is proposed in this paper. The hub and spoke are designed as integrated aluminum alloy parts, effectively eliminating the mass of hub bolts or central locking nuts.

Gear vibration and noise evaluation approaches are commonly proposed with a variety of way in a transmission system while complicated and obscured, it is difficult to provide a feasible basis for the gear development of E-drive system.

The technology of active sound generation (ASG) for automobiles is one of the most effective methods to flexibly achieve the sound design that meets the expectations of different user groups, and the active sound synthesis algorithms are crucial for the implementation of ASG. In this paper, the Kaiser window function-based the harmonic synthesis algorithm of automobile sound is proposed to achieve the extraction of the order sounds of target automobile. And, the suitable fitting functions are utilized to construct the mathematical model between the engine speed information and the amplitude of the different order sound. Then, a random phase correction algorithm is proposed to ensure the coherence of the synthesized sounds. Finally, the analysis of simulation results verifies that the established method of the extraction and synthesis of order sound can meet the requirements of target sound quality.

In recent years, research on car-like robots has received more attention due to the rapid development of artificial intelligence from diverse disciplines. As essential parts, path planning and lateral path tracking control are the basis for car-like robots to complete automation tasks. Based on the two-degree-of-freedom vehicle dynamic model, this study profoundly analyzes the car-like robots’ path planning and lateral path tracking control. Three objectives: path length, path smoothness, and path safety, are defined and used to construct a multi-objective path planning model. By introducing an adaptive factor, redefining the selection of reference points, and using the cubic spline interpolation for path determination, an improved NGSA-III is proposed, which is mostly adapted in solving the multi-objective path planning problem.

Intelligent sweeper vehicle is gradually applied to human life, in which the accuracy of garbage identification and classification can improve cleaning efficiency and save labor cost. Although Deep Learning has made significant progress in computer vision and the application of semantic network segmentation can improve waste identification rate and classification accuracy. Due to the loss of some spatial information during the convolution process, coupled with the lack of specific datasets for garbage identification, the training of the network and the improvement of recognition and classification accuracy are affected. Based on the Unet algorithm, in this paper we adjust the number of input and output channels in the convolutional layer to improve the speed during the feature extraction part. In addition, manually generated datasets are used to greatly improve the robustness of the model.

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 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.

According to the requirements of high transmission ratio and high load torque of high-speed electric drive axle planetary gear system, the design and analysis of fine-pitch planetary gear system with small modulus, small pressure angle and high full tooth height of are carried out. In order to improve the bearing capacity of gear and reduce gear meshing noise, the tooth profile modification parameters of gear system are optimized. In this paper, the tooth modification methods are analyzed and the gear train parameters are determined. The influence degree of different tooth modification methods on the transmission performance of the gear train is determined by orthogonal experiment method. The transmission error is reduced, the stress fluctuation is improved, and the gear meshing performance is greatly improved by adopting the appropriate modification scheme, which proves the effectiveness of the tooth modification scheme.

Lane detection is an important component in automatic pilot system and advanced driving assistance system (ADAS). The stability and precision of lane detection will directly determine precision of control and lane plan of vehicles. Traditional mechanical vision lane detection approaches in complicated environment have the deficiencies of low precision and feature semantic description disabilities. But the lane detection depending on deep learning, e.g. SCNN network, LaneNet network, ENet-SAD network have imbalance problems of splitting precision and storage usage. This paper proposes an approach of high-efficiency deep learning Segnet-LSTM semantic segmentation network. This network structure is composed with encoding network and corresponding decoding networks. First, convolution and maximum pooling. The proposal extracts texture details of five images and stores searching position of maximum pooling. Meanwhile, it will implement interpolate processing to the lost points.

Correct shifting schedule of vehicle coasting mode play a vital role in improving vehicle comfort and economy. At present, the calibration of the transmission shifting schedule ignores the impact of vehicle’s dynamic mass. This paper proposes a method for optimizing the shifting schedule of the coasting modes with gear based on the dynamic mass identification of the vehicle. This method identifies the dynamic mass of the vehicle during driving and substitute them into the process of solving the shifting schedule parameters. Then we get the optimal shifting schedule. At first, establish the Extended Kalman Filter to Pre-process the experimental data, reducing errors caused by excessive data fluctuations. Then, establishing a weighted squares estimation model based on particle swarm optimization to identify the dynamic mass of the vehicle.

With the rapidly developing automotive industry and stricter environmental protection laws and regulations, lightweight materials, advanced manufacturing processes and structural optimization methods are widely used in body design. Therefore, in order to evaluate and improve the pedestrian protection during a collision, this paper presents an impact simulation modeling and structural optimization method for a sport utility vehicle engine hood made of carbon fiber reinforced plastic (CFRP). Head injury criterion (HIC) was used to evaluate the performance of the hood in this regard. The inner panel and the outer panel of CFRP hood were discretized by shell elements in LS_DYNA. The Mat54-55 card was used to define the mechanical properties of the CFRP hood. In order to reduce the computational costs, just the parts contacted with the hood were modeled. The simulations were done in the prescribed 30 impact points.

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.

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.

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.

In summer, the relatively low temperature water condenses in the evaporator when the vehicle air-conditioning (AC) is running. At present, the vehicle AC condensate water without well utilization is directly wasted. The condenser’s thermal transfer performance has a great influence on the AC performance, and to increase the convective heat transfer coefficient (CHTC) is the key to its design. In this paper, a method of using atomized condensate water (CW) to enhance the condenser’s thermal transfer performance is proposed, which can make the most of the CW's cold energy. It achieves the reuse of CW and increases the condenser’s CHTC. First, the CW flow calculation model in the evaporator and the calculation model of the condenser enhanced thermal transfer using atomized CW are both set up. The influence of the evaporation degree of atomized CW particles in the air on the enhancement effect is comprehensively considered.

In these years, the advantages of using phase change material (PCM) in the thermal management of electric power battery has been wide spread. Because of the thermal conductivity of most phase change material (eg.wax) is low, many researchers choose to add high conductivity materials (such as black lead). However, the solid-liquid change material has large mass, poor flow-ability and corrosively. Therefore, it still stays on experiential stage. In this paper, the Thermal characteristics of power battery firstly be invested and the requirements of thermal management system also be discussed. Then a new PCM thermal management has been designed which uses pure water as liquid phase change material, adopts PCM with a reflux device for thermal management.

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 development of the vehicle quantity and the transportation system accompanies the rise of traffic accidents. Statistics shows that nearly 35-45% traffic accidents are due to drivers’ fatigue. If the driver’s fatigue status could be judged in advance and reminded accurately, the driving safety could be further improved. In this research, the blink frequency and eyes movement information are monitored and the statistical method was used to assess the status of the driving fatigue. The main tasks include locating the edge of the human eyes, obtaining the distance between the upper and lower eyelids for calculating the frequency of the driver's blink. The velocity and position of eyes movement are calculated by detecting the pupils’ movement. The normal eyes movement model is established and the corresponding database is updated constantly by monitoring the driver blink frequency and eyes movement during a certain period of time.

In vehicles with urea-SCR system, normal operation of the urea-SCR system and engine will be influenced if there are deposits appearing on exhaust pipe wall. In this paper, a commercial vehicle is employed to study the influence factors of deposits through the vehicle road test. The results show that, urea injection rate, temperature and flow field have impacts on the formation of deposits. When decreasing the urea injection rate of calibration status by 20%, the deposit yield would reduce by 32%. If the ambient temperature decreased from 36 °C to 26 °C, the deposit yield would increase by 95%. After optimizing the exhaust pipe downstream of the urea injector by removing the step surface, only a few flow marks of urea droplets are observed on the pipe wall, and no lumps of deposits existing.

In this research, the Mg2Si1-xSnx thermoelectric material is used in the exhaust temperature difference power-generating system, and the material's heat transfer characteristic and power-generating characteristic were analyzed. Firstly, steady heat transfer model from vehicle exhaust to cooling water was established. Then the impact of Sn/Si ratio to the thermoelectric characteristic parameter was analyzed. Finally, considering the influence of varying thermal conductivity to the heat transfer process along the material's heat transfer direction, when the cold end temperature of thermoelectric materials was controlled by cooling water respectively boiling at 343K and 373K, the thermoelectric conversion efficiency and power output of Mg2Si1-xSnx thermoelectric materials with different x value were evaluated based on simulation calculation.