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Electronic Stability Control (ESC) is an important measure to proactively guarantee vehicle safety. In this paper, the method of four-wheel hub-motor torque control is compared with the traditional single-wheel hydraulic brake control in ESC system. The control strategy adopts the hierarchical structure. In upper controller, the stability of the vehicle is identified by threshold method, the additional yaw moment control uses a way to get the moment including feedforward and feedback parts based on the linear quadratic regulator (LQR). The medium controller is tire slip rate control, in order to get the optimal target slip rate from the upper additional yaw moment, a method of quadratic programming to optimize the longitudinal force is proposed for each wheel. The inputs of tire state for the magic tire model is introduced so as to calculate the target slip rate from the target longitudinal force.

It is well-known that, compared with automatic transmissions (ATs), continuously variable transmission (CVT) shows advantages in fuel saving due to its continuous shift manner, since this feature enables the engine to operate in the efficiency-optimized region. However, as the AT gear number increases and the ratio gap narrows, this advantage of CVT is challenged. In this paper, a comparative study on fuel economy for a CVT based vehicle and a 9-speed automatic transmission (AT) based vehicle is proposed. The features of CVT and AT are analyzed and ratio control strategies for both the CVT and 9-speed AT based vehicles are designed from the view point of vehicle fuel economy, respectively. For the 9-speed AT, an optimal gear shift map is constructed. With this gear shift map, the optimal gear is selected as vehicle velocity and driving condition vary.

In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering.

Butanol, which is a renewable biofuel, has been regarded as a promising alternative fuel for internal combustion engines. When blended with diesel and applied to pilot ignited natural gas engines, butanol has the capability to achieve lower emissions without sacrifice on thermal efficiency. However, high blend ratio of butanol is limited by its longer ignition delay caused by the higher latent heat and higher octane number, which restricts the improvement of emission characteristics. In this paper, the potential of increasing butanol blend ratio by adding hot exhaust gas recirculation (EGR) is investigated. 3D CFD model based on a detailed kinetic mechanism was built and validated by experimental results of natural gas engine ignited by diesel/butanol blends. The effects of hot EGR is then revealed by the simulation results of the combustion process, heat release traces and also the emissions under different diesel/butanol blend ratios.

In the present study, we developed a reduced chemical reaction mechanism consisted of n-heptane and toluene as surrogate fuel species for diesel engine combustion simulation. The LLNL detailed chemical kinetic mechanism for n-heptane was chosen as the base mechanism. A multi-technique reduction methodology was applied, which included directed relation graph with error propagation and sensitivity analysis (DRGEPSA), non-essential reaction elimination, reaction pathway analysis, sensitivity analysis, and reaction rate adjustment. In a similar fashion, a reduced toluene mechanism was also developed. The reduced n-heptane and toluene mechanisms were then combined to form a diesel surrogate mechanism, which consisted of 158 species and 468 reactions. Extensive validations were conducted for the present mechanism with experimental ignition delay in shock tubes and laminar flame speeds under various pressures, temperatures and equivalence ratios related to engine conditions.

At present, the development of autonomous driving technology is still immature, and there is still a long way until fully driverless vehicles. Therefore, the state of the driver is still an important factor affecting traffic safety, and it is of great significance to detect the driver’s distracted behavior. In the task of driver distracted behavior detection, some characteristics of driver behavior in the cockpit can be further utilized to improve the detection performance. Compared with general human behaviors, driving behaviors are confined to enclosed space and are far less diverse. With this in mind, we propose a sparse spatiotemporal transformer which extracts local spatiotemporal features by segmenting the video at the low level of the model, and filters out local key spatiotemporal information associated with larger attention values based on the attention map in the middle layer, so as to enhance the high-level global semantic features.

Recovering the braking energy and reusing it can significantly improve the fuel economy of hybrid electric vehicles (HEVs).The battery ability of recovering electricity limits the improvement of the regenerative braking performance. As one way to solve this problem, the technology of brake-by-wire can be adopted in the HEVs to use the recovery dynamically. The use of high-power electrical equipment, such as electromechanical brake (EMB), is working in the form of brake-by-wire. Due to the nature of EMB, there exists an obvious coupling relationship between the energy flow and brake force distribution. In this paper, a brake force distribution controller is proposed in HEV with EMB, which can maximize braking energy recovery, compared with the conventional distribution control without EMB. Meanwhile, an energy flow strategy working with the distribution controller is designed, which is less limited to the performance of the battery.

With the increasingly serious problems of environmental pollution and energy shortage, electric vehicles have a promising future. As a core component of electric vehicles, the drive motor is developing towards high power density of which remains temperature rise problems, which affects the performance, efficiency and service life of the drive motor. Liquid cooling has high energy consumption and poor reliability. The heat-pipe has excellent heat conduction and temperature uniformity capabilities. Therefore, this paper proposes a heat pipe-based drive motor heat dissipation system to make the heat-pipe act on the inside of the motor to reach a specified range of driving conditions. The drive motor can better dissipate heat through the heat-pipe. Firstly, analysis of the internal heat generation mechanism of the motor, heat transfer characteristics of the heat-pipe and the heat-pipe layout plan was established.

Turbochargers can improve vehicle dynamic performance and fuel economy and are applied widely nowadays. Due to the existence of turbocharger delay effect, acceleration delay and insufficient combustion are its disadvantages. By collecting high pressure gas which generates from the inertia of the turbine in the intake passage when the vehicle slows down, the gas can be supplied for the shortage while the vehicle is accelerating, which can reduce turbocharger delay effect directly. However, turbocharger delay effect changes a little at high speed and low speed which is subjected to the air inflation and short air-release time. This paper adds a set of pressure booster device on the existing inflating-deflating device, whose thermal energy comes from the compressed air and lubricating oil, to facilitate pressure increasing in inflating-deflating device and help the chamber change sooner, which avails to relieve the delay effect.

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.

Vehicles equipped with articulated steering systems have advantages such as low energy consumption, simple structure, and excellent maneuverability. However, due to the specific characteristics of the system, these vehicles often face challenges in terms of lateral stability. Addressing this issue, this paper leverages the precise and independently controllable wheel torques of a hub motor-driven vehicle. First, an equivalent double-slider model is selected as the dynamic control model, and the control object is rationalized. Subsequently, based on the model predictive control method and considering control accuracy and robustness, a weight-variable adaptive model predictive control approach is proposed. This method addresses the optimization challenges of multiple systems, constraints, and objectives, achieving adaptive control of stability, maneuverability, tire slip ratio, and articulation angle along with individual wheel torques during the entire steering process of the vehicle.

On-road testing of driving performance of the urban bus was carried out, and a representative urban bus driving cycle was developed after on-road testing, according to the test results. Then, the vehicle simulation software AVL CRUISE was used to simulate the dynamic behavior of the urban bus. It involves the simulation of complete drive train system and the driver behavior. The model is validated by comparing the results of the simulation to the results of the field test. Then the developed driving cycle is evaluated by fuel consumption resulted from the simulation and engine bench test on fuel economy.

This work analyzes the transmission efficiency of vehicle driveline including the gearbox, universal transmission and differential. Based on the structure of transmission, mathematic models are built to analyze transmission's characteristics. However, an experiment reveals the limitation of this method. Then, the paper statistically analyzes the experimental data and mainly analyzes the influencing factors. Then Neural Network is used to build the efficiency model. A method called “filling data and gradually extrapolating” is used when building neural network model. Finally, the neural network model is used in the simulation of fuel consumption. The conclusion is Neural Network model can imitate the transmission efficiency of vehicle driveline efficiently, but its internal structure is not clear so other modeling methods are needed to be found.

Road traffic accidents resulting from alcohol-impaired driving are increasing globally despite several measures, currently in place, to curb the trend. For this reason, recent research aims at integrating alcohol early-detection systems and driving simulator experiments to identify intoxicated drivers. However, driving simulator experiments on drunk driving have focused mostly on male participants than female drivers whose characteristics have scarcely been explored. Hence in this paper, vehicle dynamic control inputs on steering, braking, and acceleration performance of 75 licensed female drivers with an upshot of alcohol at four different blood alcohol concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%) were investigated. The participants completed simulated driving in a fixed-based simulator experiment coupled with real-time ecological scenarios to extract discrete responses.

The electric vehicle motor is developing toward high power density, at the same time brings serious temperature rise problem, which affect the driving motor performance, efficiency, and useful life. Liquid cooling is usually used to solve the problem, but its energy consumption is large and the reliability is poor. In order to solve this problem, this paper proposes a heat dissipation method to improve the reliability and energy efficiency of the driving motor heat dissipation system. The method uses heat pipes heat transfer, and the heat pipes cold end are cooled by vehicle facing the wind. By establishing the motor temperature rise model, heat transfer model and vehicle dynamics model, this paper analyzes the maximum temperature region and reliability of the driving motor heat dissipation system, calculates and analyzes the efficiency of the driving motor under different driving conditions.

The articulated steering system is widely used in engineering vehicles due to its high mobility and low steering radius. The design parameters have a vital impact on the selection of the steering system assemblies, such as the operation stroke, pressure, and force of the hydraulic cylinders during the steering process, which will affect the system weight. The system energy consumption is also relevant to the geometry parameters. According to the kinetic analysis of the steering system and dynamic analysis of the steering process, the kinetic model of an engineering vehicle steering system is built, and the length and pressure variation of the cylinder is calculated and validated by the field test. The influence of the factors is analyzed based on the established model. To lower the system weight, needed pressure, and force, the multi-objective particle swarm optimization method is initiated to optimize the geometry parameter of the articulated steering system.

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.

People, vehicles and circumstances are the three key factors, which affect transportation systems. Offering more information to the driver and helping him observe on all sides so that he can make decisions correctly are of great importance for reducing accidents. According to the present traffic regulations, in this paper we focus on the rules and process used during steering and proposed to implement them in a car information central control system based on CAN. A comparison of the brake time between brake by driver and by radars revealed the great interest of using ECUs connected by CAN network.

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.

Whether the available energy of the on-board battery pack is enough for the driver’s next trip is a major contributor in slowing the growth rate of Electric Vehicles (EVs). What’s more, the actual capacity of the battery pack depend on so many factors that a real-time estimation of the state of charge of the battery pack is often difficult. We proposed a big-data based algorithm to build a battery pack dynamic model for the online state of charge estimation and a stochastic model for the energy consumption prediction. And the good performance of sensors, high-bandwidth communication systems and cloud servers make it convenient to measure and collect the related data, which are grouped into three categories: standard, historical and real-time data. First a resistance-capacitance ( RC )-equivalent circuit is taken consideration to simplify the battery dynamics.