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Flow channels in proton exchange membrane fuel cells (PEMFC) play an irreplaceable role, and flow channel design in bipolar plates is one of the most active research areas at present. The flow channel on the cathode side needs to discharge liquid water out of the fuel cell in time and allow oxygen to flow to the cathode catalytic layer as much as possible to avoid the phenomenon of cathode water flooding and mass transfer loss. In order to improve the performance of PEMFC, a method of setting both side blockages in the cathode flow channel is proposed. In this paper, lateral blockage models with three shapes are proposed to study the influence of blockage on mass transfer and performance. First, a 3D PEMFC model with a middle channel was built to calculate the fuel cell power at different discharge rates.

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.

Because of the long driving range and good power performance, plug-in hybrid electric vehicles (PHEV) have drawn much attention. And the current fuel-saving effect of PHEV still has a lot of room for improvement. The complex powertrain structure of PHEV makes the requirements for control strategy be increasing. Therefore, it is crucial to develop an efficient control strategy to ensure that the PHEV operates at optimal performance with an improved driving range. This paper establishes a mathematical model for fuel economy control of PHEV, by treating the torque distribution problem as a multi-stage decision optimization problem, and establishes a global energy management strategy based on a dynamic programming (DP) algorithm. Based on the actual physical model, this paper creatively solves the correction range of battery SOC value according to the charge and discharge power of the motor, which greatly reduces the calculation time of the DP algorithm.

Hydrogen recirculation system (HRS) is one of the main subsystems of proton exchange membrane fuel cell (PEMFC) system, and an HRS with high performance and low cost is essential to improve the fuel cell lifetime and efficiency. The ejector is becoming an effective alternative to the hydrogen circulation pump in the hydrogen recirculation system because of its small size, low cost and no parasitic power. However, the conventional ejector can only operate at the limited output power of the fuel cell. In order to improve this drawback, a hydrogen recirculation system with a separator-ejector integrated device is proposed. The hydrogen recirculation system based on the integrated device can make the space more compact, reduce the condensation effect of the piping, improve the fuel cell performance and reduce the cost. The design and integration method of the ejector and gas-water separator in this hydrogen recirculation system are introduced.

Regenerative braking is an effective way to increase the cruising range of vehicles. In commercial vehicles with large vehicle mass, regenerative braking can be maintained in a high-power working state for a long time theoretically because of the large braking torque and long braking time. But in fact, it is often impossible to run at full power because of battery safety problems. In this paper, a control strategy is designed to maintain the maximum power operation of regenerative braking as much as possible. The maximum charging power of the battery is obtained through the battery model, and it is set as the battery limiting parameter. The regenerative braking torque and power are obtained by using the motor model. The eddy current retarder is used to absorb the excess power that the battery can't bear, and the braking torque of the eddy current retarder is calculated. Finally, mechanical braking is used to make up the insufficient braking torque.

With the improvement of sensor accuracy, sensor data plays an increasingly important role in intelligent vehicle motion control. Good use of sensor data can improve the control of vehicles. However, data-based end-to-end control has the disadvantages of poorly interpreted control models and high time costs; model-based control methods often have difficulties designing high-fidelity vehicle controllers because of model errors and uncertainties in building vehicle dynamics models. In the face of high-speed steering conditions, vehicle control is difficult to ensure stability and safety. Therefore, this paper proposes a hybrid model and data-driven control method. Based on the vehicle state data and road information data provided by vehicle sensors, the method constructs a deep neural network based on LSTM and Attention, which is used as a compensator to solve the performance degradation of the LQR controller due to modeling errors.

This paper addresses the brake pad particle emission during the braking process of a vehicle in motion. The frictional-constant contact between the disc brake and pads results in an increased temperature and wear of the pads. The emission of brake pad particles into the atmosphere leads to an increase in air pollution and hence becomes hazardous to the human body. In this paper, a wheel brake disc is installed in a ventilation system where the specific air flow is introduced in order to investigate the thermal performance and the emission of particles from the brake pads. A mathematical model using the fundamental parameters of the brake disc and ventilation system is established. The behavior of the heat transfer is studied using computational fluid dynamics (CFD). The particle emission rate from the pads is calculated under the assumption of uniform constant pressure distribution at the contact surface of the brake disc and pad.

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 plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PHEV to a certain extent. First, on the basis that MATLAB software has completed the modeling of the key components of the vehicle, the fuzzy controller of the vehicle is established considering the principle of the joint control of the engine and the electric motor.

Radiative cooling uses the cold space source to cool the object. The radiative cooling film prepared based on the principle can reduce the fuel consumption of automobile air conditioning refrigeration. In this paper, according to the passive radiative cooling principle, taking SiO2 as the radiative cooling film of infrared radiation material, the theoretical cooling value of the passenger compartment of the automobile is calculated and analyzed based on the heat balance equation. The influence of radiative cooling film on the temperature field of passenger cabins was studied by finite element analysis. The results show that the cooling film made of SiO2 as passive radiation material has an apparent cooling effect on the passenger cabins. At the ambient temperature of 35.15°C, the theoretical cooling temperature is 6.7K. When the radiative cooling film is applied to automobiles, the cooling value of the passenger cabin body, seat, instrument panel, and other parts reaches 2.2K-5.1K.

For series hybrid electric vehicles (SHEV), rule-based strategies are realistic and powerful in real-time applications. However, the previous rule-based strategy cannot strike a balance between the best fuel economy and the best battery performance while maintaining the advantages of real-time applications. In order to obtain higher efficiency and reduce battery consumption, we have developed an adaptive hybrid thermostat strategy. On the basis of maintaining the load leveling of the thermostat strategy, the threshold-changing mechanism is added to realize the adaptive adjustment of the engine starting power under different SOC conditions, so as to achieve the goal of prolonging the battery life. In addition, the more fuel-efficient emergency handling rules designed to further reduce comprehensive fuel consumption.

In order to study the influence of low-viscosity oil on automobile pollutant emissions reduction, three different 0W20 oil samples were prepared with oil 5W30 as the base oil. Parameters such as the oil viscosity, ash, and element content were tested at different stages, speeds, and accelerations of the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The results showed the effects of low-viscosity oil on exhaust emissions reduction were mainly concentrated in the low-speed and extra high-speed segment. At the low-speed segment, especially in the starting stage, carbon monoxide (CO), total hydrocarbon (THC), and non-methane hydrocarbon (NMHC) emissions can be reduced. The use of low ash oil can reduce nitrogen oxides (NOx) emissions; the methane (CH4) emissions can be reduced by increasing the Zinc (Zn) content in engine oil moderately.

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.

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.

When driving in mountainous areas, vehicles often encounter long downhill sections. Due to the large mass of bus and the drum brake with poor heat dissipation effect, it is easy for bus to produce braking thermal decay in long downhill section, which makes the vehicle out of control and causes safety accidents. The braking methods of parallel hybrid electric bus include drum braking, engine braking and regenerative braking, whose torque models are established in this paper. The coasting test in Trucksim is used to verify the correctness of the engine braking torque model. Based on coupling braking torque curve with vehicle speed in different gradient, the stable speed is determined and the shift strategy is proposed. The temperature rise model of brake drum is established to analyze the temperature change of brake drum during long downhill. Then, according to the ramp data of G22 freeway, the above models are simulated.

Heavy commercial vehicle drivers may frequently shift gears when they are running on long and downhill roads in mountainous area. In order to improve driving safety and fuel economy, it is necessary to predict the slope of the road ahead in real time and correct the driver's shift strategy in time. At present, the road slope estimation is mainly based on the real-time estimation of the road slope at the current position of the vehicle based on the vehicle driving information obtained by the sensors, but the road slope of the road section that the vehicle is about to reach has not been predicted. In this paper, based on the road slope information of the road section that the driver has driven through, combined with Geographic Information System (GIS) information and road design standards, the slope of the road section ahead is predicted.

The mountain roads are curved and complicated, with undulating terrain and large distance between charging stations. Compared with traditional powered vehicles, in addition to safety issues, pure electric vehicles also need to deal with the driving range issue. At present, the relevant researches on automobile driving in mountainous areas mainly focus on the driving safety of traditional fuel oil vehicles when going uphill and downhill, while there are few researches on the driving planning of pure electric commercial vehicles on curved slope road. This paper presents a speed planning method for pure electric commercial vehicles based on vehicle-road collaboration technology. First, establish the vehicle dynamics model, analyze the vehicle dynamics characteristics when passing the downhill curve, calculate the safe speed range of the vehicle when passing the downhill curve, and establish the safe speed model of the downhill curve.

Lane changing manoeuvers is an essential rudiment in vehicle driving and has a significant impact on the characteristics of traffic flow. In the case of traditional cars, the driver operates the vehicle to complete the lane change whilst for autonomous vehicles, completing the lane change requires planning the lane change trajectory and controlling the vehicle speed during the lane change. Unreasonable lane change trajectory and vehicle speed may cause the vehicle to lose stability, threaten driving safety, increase energy consumption and waste energy. This paper considers the safety and economy of the lane changing process, and proposes a new lane changing method for vehicles.

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.

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.