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The installation of the Electronic Braking System (EBS) could effectively improve braking response speed, shorten braking distance, and ensure driving safety of commercial vehicles. However, during longitudinal deceleration control process, the commercial vehicles face not only challenges such as large inertia mass and random road gradient resistance of the vehicle layer, but also non-linear characteristics of the EBS actuator layer. In order to solve these problems, this paper proposes a commercial vehicle’s longitudinal deceleration precise control strategy considering vehicle-actuator dynamic characteristics. First, longitudinal dynamics of commercial vehicle is analyzed, and so is the EBS’ non-linear response hysteresis characteristics. Then, we design the dual layer deceleration control strategy. In vehicle layer, the recursive least squares with forgetting factor and Kalman filtering are comprehensively applied to dynamically estimate the vehicle mass and driving road slope.

Ambient temperature is a very sensitive use condition for electric vehicles (EVs), so it is imperative to ensure the maintenance of suitable temperature. This is particularly important in regions characterized by prolonged exposure to unfavorable temperature conditions. In such cases, it becomes necessary to implement insulation measures within parking facilities and allocate energy resources to sustain a desired temperature level. Solar energy is a renewable and environmentally friendly source of energy that is widely available. However, the effectiveness of utilizing solar energy is influenced by various factors, such as the time of day and weather conditions. The use of phase change material (PCM) in a latent heat energy storage (LHES) system has gained significant attention in this field. In contrast to single-phase energy storage materials, PCM offer a more effective heat storage capacity.

Velocity prediction on hilly road can be applied to the energy-saving predictive control of intelligent vehicles. However, the existing methods do not deeply analyze the difference and diversity of road slope driving characteristics, which affects prediction performance of some prediction method. To further improve the prediction performance on road slope, and different road slope driving features are fully exploited and integrated with the common prediction method. A rolling prediction-based multi-scale fusion prediction considering road slope transition driving characteristics is proposed in this study. Amounts of driving data in hilly sections were collected by the advanced technology and equipment. The Markov chain model was used to construct the velocity and acceleration joint state transition characteristics under each road slope transition pair, which expresses the obvious driving difference characteristics when the road slope changes.

Intake system is an important noise source for commercial vehicles, which has a significant impact on their NVH performance. To predict the intake noise more accurately, a new one-dimensional prediction model is proposed in this paper. An air compressor model is introduced into the traditional model, and the acoustic properties of the intake system are simulated by GT-power. The simulation data of the inlet noise is obtained to make a comparison with the inlet noise data acquired from a test. The result shows that the proposed model can make a more precise prediction of the inlet noise. Compared with the traditional model, the proposed model can identify the noise coming from the air compressor, and achieve a more accurate prediction of the total sound pressure level of the inlet noise.

Considering the change of vehicle future power demand in the process of energy distribution can improve the fuel saving effect of hybrid system. However, current studies are mostly based on historical information to predict the future power demand, where it is difficult to guarantee the accuracy of prediction. To tackle this problem, this paper combines hybrid energy management with predictive cruise control, proposing a hierarchical control strategy of predictive energy management (PEM) that includes two layers of algorithms for speed planning and energy distribution. In the interest of decreasing the energy consumed by power components and ensuring transportation timeliness, the upper-level introduces a predictive cruise control algorithm while considering vehicle weight and road slope, planning the future vehicle speed during long-distance driving.

Unmanned Ground Vehicle (UGV) has a wide range of applications in the military, agriculture, firefighting and other fields. Path planning, as a key aspect of autonomous driving technology, plays an essential role for UGV to accomplish the established driving tasks. At present, there are many global path planning algorithms in grid maps on unstructured roads, while general grid maps do not consider the specific elevation or ground type difference of each grid, and unstructured roads are generally considered as flat and open roads. On the contrary, the unmanned off-road is always a bumpy road with undulating terrain, and meanwhile, the landform is complex and the types of features are diverse. In order to ensure the safety and improve the efficiency of autonomous driving of UGV in off-road environment, this paper proposes a global off-road path planning method for UGV based on the raw image of remote sensing map. Firstly, the raw image is gridded.

It is generally considered that the material properties of foam are the most important factors in vehicle seat, which affect the human-seat interface pressure. Therefore, only the role of foam is usually considered when the finite element method is used to simulate the human-seat interface pressure. In this paper, the mechanical properties and the modeling method of commonly used seat cover material were studied. The models of the seat with and without cover were established respectively according to the real-vehicle seat geometric data, and the human-seat interface pressure was simulated after the seat and human model consisting of bones, soft tissue and skin were assembled. The simulation result was compared with the actual measurement results from test, which verified the accuracy of the simulation and the role of seat cover in the human-seat interface pressure simulation.

Autonomous driving technology, as the product of the fifth stage of the information technology revolution, is of great significance for improving urban traffic and environmentally friendly sustainable development. Autonomous driving can be divided into three main modules. The input of the decision module is the perception information from the perception module and the output of the control strategy to the control module. The deep reinforcement learning method proposes an end-to-end decision-making system design scheme. This paper adopts the Deep Deterministic Policy Gradient Algorithm (DDPG) that incorporates the Priority Experience Playback (PER) method. The framework of the algorithm is based on the actor-critic network structure model. The model takes the continuously acquired perception information as input and the continuous control of the vehicle as output.

Taking an off-road vehicle equipped with 32-speed binary logic automatic transmission (AT) as the research object, the slope starting control research is carried out. The slope starting process is divided into the overcoming resistance stage, the sliding friction stage, and the synchronization stage. The control strategies for each stage are designed respectively. Focusing on the control of the sliding friction stage, the equivalent two-speed model of the starting clutch is established, which realizes the calculation of the speed difference and the slip rate between the driving and driven ends of the starting clutch. Furthermore, the slope starting control strategy based on the proportional-integral-derivative (PID) control of the clutch slip rate is designed. Through the simulation tests of the vehicle starting at different slopes, the correctness of the slope starting control strategy has been verified by MATLAB/Simulink.

Aiming at the low transmission efficiency and power density of the hydraulic automatic transmission (AT), and the increasingly complex structure of its planetary gear with the increase of transmission gears, this paper proposes a new type of binary logic transmission (BLT), which adopts the double internal meshing planetary row (DIMPR), based on a heavy-duty commercial vehicle. By introducing the concept of BLT and analyzing the transmission performance of the DIMPR, the process of scheme design of binary double internal meshing planetary gear transmission (BDIMPGT) is established. According to the structural characteristics of the DIMPG, the support structure of the planetary gear is designed based on CAD and CATIA. In the structural design of binary clutches, V-groove clutch parts are coupled to the transmission case, planetary carrier, and sun shaft, respectively, in each DIMPG.

With the development of intelligent and electric vehicles, higher requirements are put forward for the active braking and regenerative braking ability of the braking system. The traditional braking system equipped with vacuum booster has difficulty meeting the demand, therefore it has gradually been replaced by the integrated braking system. In this paper, a novel Integrated Braking System (IBS) is presented, which mainly contains a pedal feel simulator, a permanent magnet synchronous motor (PMSM), a series of transmission mechanisms, and the hydraulic control unit. As an integrative system of mechanics-electronics-hydraulics, the IBS has complex nonlinear characteristics, which challenge the accurate pressure control. Furthermore, it is a completely decoupled braking system, the pedal force doesn’t participate in pressure-building, so it is necessary to precisely identify driver’s braking intention.

The purpose of this study is to evaluate the impact of two-stage pilot injection parameters on the combustion and emissions of pilot diesel compression ignition natural gas (CING) engine at low load. Experiments were performed using a diesel/natural gas dual-fuel engine, which was modified from a six-cylinder diesel engine. The effect of injection timing and injection pressure of two-stage pilot diesel were analyzed in order to reduce both the fuel consumption and total hydrocarbon (HC) and carbon monoxide (CO) emissions under low load conditions. The results indicate that, because injection timing can determine the degree of pilot diesel stratification, in-cylinder thermodynamic state, and the available mixing time prior to the combustion, the combustion process can be controlled and optimized through adjusting injection timing.

Based on traditional heavy commercial vehicles, a hydraulic hub-motor drive vehicle (HHMDV) is equipped with a set of hydraulic hub-motor auxiliary system (HHMAS) to improve the traction performance and adaptability under complex conditions. In the case of low-speed operation or mechanical transmission failure, the creep mode (CM) can be used to drive the vehicle. Aiming at a common hydraulic system problem that flow loss increases due to temperature variation, a temperature compensation control strategy of the CM is proposed in this paper. By analyzing the speed regulation characteristics of the closed loop of the system in the CM, combined with the efficiency of the hydraulic variable pump (HP) and the hydraulic quantitative motor (HM), and aiming at adjusting the engine work in the optimal curve of the engine, the temperature compensation factor is introduced to control the HP displacement with hydraulic stepless speed regulation.

Based on the traditional heavy commercial vehicle, hydraulic hub-motor drive vehicle (HHMDV) is equipped with a hydraulic hub-motor auxiliary drive system, which makes the vehicle change from the rear-wheel drive to the four-wheel drive to improve the traction performance on low-adhesion road. In the typical operating mode of the vehicle, the leakage of the hydraulic system increases because of the oil temperature rising, this makes the control precision of the hydraulic system drop. Therefore, a temperature compensation control strategy for the assist mode is proposed in this paper. According to the principle of flow continuity, considering the loss of the system and the expected wheel speed, the control strategy of multifactor target pump displacement based on temperature compensation is derived. The control strategy is verified by the co-simulation platform of MATLAB/Simulink and AMESim.

The Electro-Mechanical Brake Booster system (EMBB) is a kind of novel braking booster system, which integrates active braking, regenerative braking, and other functions. It usually composes of a servo motor and the transmission mechanism. EMBB can greatly meet the development needs of vehicle intelligentization and electrification. During active braking, EMBB is required to respond quickly to the braking request and track the target pressure accurately. However, due to the highly nonlinearity of the hydraulic system and EMBB, traditional control algorithms especially for PID algorithm do not work well for pressure control. And a large amount of calibration work is required when applying PID algorithms to pressure control in engineering.

In order to solve the coupling problems between braking safety, economical efficiency of braking and the comfort of drivers, a braking control strategy based on Electronically Controlled Braking System (EBS) and intelligent network technology under non-emergency braking conditions is proposed. The controller utilizes the intelligent network technology’s characteristics of the workshop communication to obtain the driving environment information of the current vehicle firstly, and then calculate the optimal braking deceleration of the vehicle based on optimal control method. The strategy will distribute the braking force according to the ideal braking force distribution condition based on the EBS according to the braking deceleration; the braking force will be converted to braking pressure according to brake characteristics. Computer co-simulations of the proposed strategy are performed, the strategy is verified under different initial speeds.

The purpose of this paper is to improve the path-following capability and high-speed lateral stability of the articulated heavy vehicles (AHVs). The six-axle heavy articulated vehicle was taken as the research object, in order to simplify the control design, the three-axle trailer of the articulated vehicles was simplified to a single-axle trailer. The Newton's second law was applied to the tractor unit and the single-axle trailer unit respectively, a three-degree-of-freedom vehicle yaw plane model was established, and its state space equation was derived. The trailer steering controller was designed by linear quadratic regulator (LQR) technique. At the same time, the optimal index function was determined by combining the vehicle state variables, and the optimal control input was obtained by using the algebraic Riccati equation.

The underbody diffusers are used widely in race cars to improve the flow field structure at the bottom of the car and provide enough downforce. In recent years, passenger cars have begun to use bottom diffuser to improve aerodynamic characteristics, so as to reduce drag and increase downforce. In this paper, the aerodynamic characteristics of the bus with different underbody diffuser angles and channel numbers are studied by numerical simulation analysis. Firstly, the aerodynamics of the bus under different diffuser inlet and outlet angles are studied, and then an optimal inlet and outlet angle is determined based on the simulation results. Then, using this angle as a constant, the 2, 3, and 4 channel numbers were chosen as the diffuser channel variables to study the influence of the multiple-channel diffusers on the aerodynamic drag of the vehicle.

The Electronic Stability Program (ESP), as a key actuator of traditional automobile braking system, plays an important role in the development of intelligent vehicles by accurately controlling the pressure of wheels. However, the ESP is a highly nonlinear controlled object due to the changing of the working temperature, humidity, and hydraulic load. In this paper, an accurate pressure control strategy of single wheel during active braking of ESP is proposed, which doesn’t rely on the specific parameters of the hydraulic system and ESP. First, the structure and working principle of ESP have been introduced. Then, we discuss the possibility of Pulse Width Modulation (PWM) control based on the mathematical model of the high-speed switching valve. Subsequently, the pressure building characteristics of the inlet and outlet valves are analyzed by the hardware in the Loop (HiL) experimental platform.

As a critical part of auto-body, the design of tailgate not only affects the beauty, usability and safety of automobile, but also involves more and more issues about environmental protection and energy saving. Hence, it is of vital importance to investigate lightweight of tailgate. This paper mainly focuses on lightweight design of CFRP tailgate based on conventional SUV metal tailgate, which can be realized under the condition of meeting requirements of stiffness, modal and manufacturing with the adoption of multi-step optimization method. To start with, finite element (FE) model of metal tailgate is established. Meanwhile, the stiffness and modal analyses, including bending stiffness, torsional stiffness, lateral stiffness, vertical stiffness and free modal are set up. Then, the structural performances of metal tailgate are analyzed, and the topology optimization of CFRP tailgate is performed.