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A flow channel design of the battery liquid cooling plate is carried out through the variable density topology optimization method according to the heat dissipation requirements of lithium-ion power batteries under actual working conditions. Firstly, given the non-uniform heat generation of lithium battery cells, the heat generation mechanism is studied so that the battery electro-thermal model is established, then the distribution regularity of heat generation rate in the cell at different discharge rates is obtained. Subsequently, through COMSOL Multiphysics simulation software, the multi-objective topology optimization of the primary configuration radiator is conducted. The weights of the optimization objectives minimum temperature and minimum flow resistance are determined by practical engineering application. Finally, an optimized model with a volume fraction of 50% was obtained.

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.

In order to obtain the comprehensive evaluation of thermal management system for the retarder, the complete driveline thermal management model is built. The characteristic parameters for the thermal management system are determined and the hydromechanical characteristics for the retarder are fixed by the rig test. On the basis of the same whole vehicle driving cycle, comparing to the traditional mechanical-drive system, the independent-drive system makes the working temperature of the heat source more stable. Meanwhile the parasitic power caused by the radiator fan is decreased markedly on the condition that the heat reject requirement of the heat source is satisfied.

The cooling system with two fans is generally driven by electrical motors in the small cars. Compared with the traditional cars, heavy duty trucks have the larger heat dissipation power of cooling system. The motors power consumption of dual fans will be larger and the two electrical motors will occupy a large space in the engine cabin. Hydrostatic drive refers to the cooling fan is driven by hydraulic motor, but it has the low transmission efficiency. According to the engine water temperature value and the actual working status of the hydraulic system, the actual speed of cooling fan can be controlled by the computer, which guarantees the normal working water temperature of the engine. Hydrostatic drive is generally applied to heavy vehicles, engineering machinery and excavators as driving source of cooling fan which contains the advantages of large output power, overload protection, continuous speed regulation and flexible space arrangements.

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.

Coolant flow and its heat transfer directly affect the cooling efficiency, thermal load of heated components as well as thermal efficiency of diesel engine. An efficient approach to study cooling system for diesel engine is 3D CFD calculation for coolant jacket and 1D cooling system simulation. The velocity, pressure and heat transfer coefficients (HTC) distribution in the coolant jacket of a 4 cylinder diesel engine are computed by 3D CFD approach using AVL/FIRE software. The improved schemes can be put forward according to calculating results. The boundary condition of 1D cooling system for diesel engine can be obtained by averaging computed inlet and outlet total pressure drop and heat transfer coefficients from CFD calculation. The parameters of the engine, which are fitted with the vehicle such as capacity of radiator, fan and water pump, could be decided.

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.

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.

The battery liquid cooling system can ensure that the battery works within a suitable temperature range, improve the safety performance of the battery system, and ensure the cruising range. This paper introduces a design scheme of a stamped double-parallel liquid cooling plate. Based on the STAR-CCM+ simulation software, a thermal simulation model of the battery management system is established to analyze the thermal behavior of the battery system and to study the effect of the inlet mass flow rate on the temperature of the top surface of the batteries. At the same time, with the analysis of the proportion of pressure drop of each component in the liquid cooling plate, an optimization of inserted part in the liquid cooling plate is proposed. The numerical analysis results are compared with the experimental results of the pressure drop to improve the effectiveness of the optimization scheme.

The heavy duty trucks have large engine power and drive continuously in mountainous area, so the heat dissipation of engine is very important. In the traditional cooling system with fixed transmission ratio fan, the cooling capacity is insufficient and the engine is easy to be over-heated when the engine is working in low speed and heavy load conditions. Owning to the bigger size of electric motor compared to the hydraulic motor, it is not suitably applied to the heavy duty trucks. Contrasted with the electric motor, the hydraulic drive cooling system is widely applied in heavy duty trucks due to smaller size, larger power, continuous speed modulation and flexible installation location. However, the low transmission efficiency of the pump-motor system results in high power consumption of the cooling system. In this paper, the mathematical and simulation model of hydraulic-driven fan cooling system is established for the specific engine.

At present, most of the longitudinal car-following control algorithms based on model predictive control (MPC) do not consider the influence of the presence of the sloping road on the inter-vehicle distance, resulting in poor tracking capability under ramp conditions. In order to reduce the inter-vehicle distance error under ramp conditions and improve the tracking capability of longitudinal car-following control algorithm. The car-following control algorithm based on MPC considering uphill and downhill is proposed. This algorithm is based on the vehicle structure of fuel passenger cars, and adds a slope angle reconstruction module for implementing slope angle measurement and reducing the complexity of slope angle calculation based on the framework of conventional hierarchical control structure.

The automatic emergency braking (AEB) system is an important part of automobile active safety, which can effectively reduce rear-end collision accidents and protect drivers' safety through active braking. AEB system has been included in many countries' new car assessment programme as the test content of active safety. In view of obviously deficiencies of the existing AEB control algorithm in avoiding longitudinal collision at high speed, it is proposed to an optimized model of the minimum safe distance for rear-end collision prevention on high-speed road in order to improve the accuracy of AEB system. Considering the influence of road adhesion coefficient and human comfort on the maximum braking deceleration, it is established to a more accurate and reasonable AEB system to avoid collision for expressway. The collision avoidance strategy is verified by simulation software.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.

Preventing skidding is essential for studying the safety of driving in curves. However, the adhesion of the vehicle during the driving process on the wet and slippery road will be significantly reduced, resulting in lateral slippage due to the low adhesion coefficient of the road surface, the speed exceeding the turning critical, and the turning radius being too small when passing through the corner. Therefore, to reduce the incidence of traffic accidents of passenger cars driving in curves on rainy and snowy days and achieve the purpose of planning safe driving speed, this paper proposes a curve active safety system based on a deep learning algorithm and vehicle dynamics model. First,we a convolutional neural network (CNN) model is constructed to extract and judge the characteristics of snow and ice adhesion on roads.

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.