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Compared to traditional vehicles, four-wheel independent drive and four-wheel independent steering (4WID-4WIS) vehicles have gained significant attention from researchers due to their enhanced control flexibility and superior handling performance. The steering angle deviation caused by dynamic toe angle changes in two-wheel steering (2WS) systems is often minimal and hence overlooked. However, the impact becomes notably significant in 4WIS systems. This article contrasts the tire slip angle differences between 2WS and 4WIS, and delves into the effects of dynamic toe angle variations on 4WIS control. Solutions are proposed both in terms of steering angle control and suspension design. Firstly, a dynamic model for the 4WID-4WIS vehicle is established. Secondly, a hierarchical tire force distribution strategy is designed for trajectory tracking.

Lane changing is an essential action in commercial vehicles to prevent collisions. However, steering system malfunctions significantly escalate the risk of head-on collisions. With the advancement of intelligent chassis control technologies, some autonomous commercial vehicles are now equipped with a four-wheel independent braking system. This article develops a lane-changing control strategy during steering failures using torque vectoring through brake allocation. The boundaries of lane-changing capabilities under different speeds via brake allocation are also investigated, offering valuable insights for driving safety during emergency evasions when the steering system fails. Firstly, a dual-track vehicle dynamics model is established, considering the non-linearity of the tires. A quintic polynomial approach is employed for lane-changing trajectory planning. Secondly, a hierarchical controller is designed.

The strategy for emission reduction in the P2.5 hybrid system involves the optimization of engine torque, engine speed, catalyst heat duration, and motor torque regulation in a coordinated manner. In addition to employing traditional engine control methods used in HEV models, unique approaches can be utilized to effectively manage emissions. The primary principle is to ensure that the engine operates predominantly under steady-state conditions or limits its load to regulate emissions levels. The main contributions of this paper are as follows: The first is the optimization of catalyst heating stage. During the catalyst heating stage, the system divides it into one or two stages. In the first stage, the vehicle is driven by the motor while keeping the engine idle. This approach stabilizes catalyst heating and prevents fluctuations in air-fuel ratio caused by speed and load changes that could potentially worsen emissions performance.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

With the rapid advancement in intelligent vehicle technologies, comprehensive environmental perception has become crucial for achieving higher levels of autonomous driving. Among various perception tasks, monitoring road types and evenness is particularly significant. Different road categories imply varied surface adhesion coefficients, and the evenness of the road reflects distinct physical properties of the road surface. This paper introduces a two-stage road perception framework. Initially, the framework undergoes pre-training on a large annotated drivable area dataset, acquiring a set of pre-trained parameters with robust generalization capabilities, thereby endowing the model with the ability to locate road areas in complex regions.

In order to realize the series-parallel switching control of hybrid electric vehicle (HEV) with dual-motor hybrid configuration, a method of unpowered interrupt switching based on the coordinated control of three power sources was proposed by analyzing the series-parallel driving mode of the dual-motor hybrid configuration. The series to parallel switching process is divided into three stages: speed regulation stage, clutch combination and power source switching. The distribution control of speed regulating torque is carried out in the speed regulating stage. The speed adjustment torque is preferentially allocated to the power source of the input shaft (engine and P1) to carry out the lifting torque. Due to the high speed adjustment accuracy and fast response of the P1 motor, the input shaft is preferentially allocated to P1 for speed adjustment, that is, the torque intervention of P1.

In order to solve the problems of the shuffle caused by internal and external excitation and the difficulty in obtaining the real-time accurate engine torque during the parallel mode operation of hybrid electric vehicles, a dynamic coordination control strategy for suppressing the jitter of hybrid electric vehicles based on the closed-loop control of engine speed was proposed. The engine torque filtering control method based on the slope limit was adopted to limit the rate of change of the engine torque and reduce the impact caused by the sudden change of the engine torque; the engine speed closed-loop control method was used to take the motor speed which is easy to be measured accurately in real time as the feedback control variable, which solved the problem of the real-time accurate estimation of the engine torque online. In parallel mode, the motor torque accounts for a small proportion because the torque distribution method gives priority to the engine.

In hybrid vehicles, the drive motor is directly connected to the drive train and the inherent drive train damping is low. When subjected to external disturbance, the low damping characteristics of the transmission system may cause torsional vibration, which will continue to oscillate the transmission system and affect the driving performance of the vehicle. In this paper, we propose a harmonic injection wheel control method based on motor speed to suppress oscillations and improve the driving performance of hybrid electric vehicles. The harmonic injection control method based on motor speed is based on Fourier transform to decompose sinusoidal harmonics based on specific order of motor speed. RLS algorithm is used to estimate the amplitude and phase, and PI control is used to calculate the compensation torque for the actual amplitude and target amplitude. Simulation and test results show that the proposed control strategy is effective in suppressing oscillations.

Ammonia (NH3), a zero-carbon fuel, has great potential for internal combustion engine development. However, its high ignition energy, low laminar burning velocity, narrow range of flammability limits, and high latent heat of vaporization are not conducive for engine application. This paper numerically investigates the feasibility of utilizing ammonia in a heavy-duty diesel engine, specifically through low-pressure direct injection (LP-DI) of hydrogen to ignite ammonia combustion. Due to the lack of a well-corresponding mechanism for the operating conditions of ammonia-hydrogen engines, this study serves only as a trend-oriented prediction. The paper compares the engine's combustion and emission performance by optimizing four critical parameters: excess air ratio, hydrogen energy ratio, ignition timing, and hydrogen injection timing. The results reveal that excessively high hydrogen energy ratios lead to an advanced combustion phase, reducing indicated thermal efficiency.

Turbulent jet ignition (TJI) combustion using pre-chamber ignition can accelerate the combustion speed in the cylinder and has garnered growing interest in recent years. However, it is complicated for the optimization of the pre-chamber structure and combustion system. This study investigated the effects of the pre-chamber structure and the intake ports on the combustion characteristics of a gasoline engine through CFD simulation. Spark ignition (SI) combustion simulation was also conducted for comparison. The results showed that the design of the pre-chamber that causes the jet flame colliding with walls severely worsen the combustion, increasing the knocking intendency, and decrease the thermal efficiency. Compared with SI combustion mode, the TJI combustion mode has the higher heat transfer loss and lower unburned loss. The well-optimized pre-chamber can accelerate the flame propagation with knock suppression.

The driving risk field model offers a feasible approach for assessing driving risks and planning safe trajectory in complex traffic scenarios. However, the conventional risk field fails to account for the vehicle size and acceleration, results in the same trajectories are generated when facing different vehicle types and unable to make safe decisions in emergency situations. Therefore, this paper firstly introduces the acceleration and vehicle size of surrounding vehicles for improving the driving risk model. Then, an integrated decision-making and planning model is proposed based on the combination of the novelty risk field and model predictive control (MPC), in which driving risk and vehicle dynamics constraints are taken into consideration. Finally, the multiple driving scenarios are designed and analyzed for validate the proposed model.

Ammonia is employed as the carbon-free fuel in the future engine, which is consistent with the requirements of the current national dual-carbon policy. However, the great amount of NOx and unburned NH3/H2 in the exhaust emissions is produced from combustion of ammonia and is one kind of the most strictly controlled pollutants in the emission regulation. This paper aims to investigate the NOx and unburned NH3/H2 generative process and emission characteristics by CFD simulation during the engine combustion. The results show that the unburned ammonia and hydrogen emissions increase with an increase of equivalence ratio and hydrogen blending ratio. In contrast, the emission concentrations of NOx, NO, and NO2 decrease with the increasing of equivalence ratio, but increase with hydrogen blending ratio rising. The emission concentration of N2O is highly sensitive to the O/H group and temperature, and it is precisely opposite to that of NO and NO2.

Applications in commercial and military fields created high demands on the steering performance of multi-axle vehicle. With the characteristic of more degrees of freedom (DOF), all-wheel cooperative steering is more conducive to improve the steering performance of multi-axle vehicle. This paper studies multi-axle vehicle assembled with steer-by-wire system, and proposes a control strategy to achieve all-wheel cooperative steering to improve the low-speed steering flexibility and high-speed steering stability of multi-axle vehicle. Based on the ideal steering performance at low-speed and high-speed, the steady-state gain of multi-axle vehicles at different speeds is reshaped. Also, the corresponding vehicle reference model is constructed to provide the ideal vehicle state as a reference. The precision of the vehicle reference model is verified by an all-wheel independent steering platform.

In recent years, the tractor-semitrailer combination has become the primary vehicle of China's long-distance freight system. In this paper, with the aim of optimizing the path tracking control and following control of the tractor-semitrailer combination, a kinematics-based path tracking control scheme is proposed. Firstly, a kinematic model of the tractor-semitrailer combination has been constructed. The control of the tractor-semitrailer combination is simplified to focus on three control points based on the kinematics model. Secondly, the path tracking control algorithm and the following control algorithm of the tractor-semitrailer combination are proposed in this paper. The improved MPC is used for path-tracking control of tractor-semitrailer combinations. The cost function of rolling optimization steps is intended, and the optimal line is determined with the lateral deviation, the variation of lateral error, and the deviation of heading angle as the input.

Accurate identification of driver’s braking intention is essential in advanced driver assistance system and can make the driving process more comfortable and trustworthy. In this paper, a novel method for driver braking intention identification in cut-in scenarios was proposed by using driver’s gaze information and motion information of cut-in vehicles. Firstly, a "looking in and looking out" experimental platform including three eye-tracking cameras and one front-view camera was built to collect driver's gaze information and the vehicle motion information. Secondly, driver’s gaze features and motion features of cut-in vehicles were selected and the braking intention identification performance of several decision tree-based ensemble learning algorithms was compared. Thirdly, the feature importance was analyzed by using SHAP (SHapley Additive exPlanations) values. This novel method of braking intention identification makes full use of in-vehicle camera sensors.

In order to improve the ignition capacity and burning rate for spark-ignited engines, pre-chamber jet ignition is a promising technique to achieve fast premixed combustion and low pollutant emissions. However, few studies focus on the interaction between multiple reacting (i.e. flamelet) or reacted (i.e. radical) jets, its effect on ignition, exotherm and flow behaviors also remain to be revealed. This paper investigated two types of jet interaction under different pre-chamber structures, including the jet-crossing and unequal nozzle designs. Optical experiments under different conditions were conducted in a constant volume combustion chamber with CH4 as fuel, using simultaneous high speed schlieren and OH* chemiluminescence method. Meanwhile, computational fluid dynamics (CFD) simulations with CH4 and NH3/CH4 blend fuels were carried out using Converge software to provide further insights of turbulent flow and ignition process.

To tackle the over-actuated and highly nonlinear characteristics that four-wheel-independent-steering and four-wheel-independent -driving (4WIS/4WID) vehicles exhibit when tracking aggressive trajectory, a hierarchical controller with layers of computation-intensive modules is commonly adopted. The high-level linear motion controller commands the desired state derivatives of the vehicle to meet the overall trajectory tracking objectives. Then the system dynamic is inversed by the mid-level control allocation layer and the low-level wheel control layer to map the target state derivatives to steering angle and motor torque commands. However, this type of controller is difficult to implement on the embedded hardware onboard since the nonlinear dynamic inversion is typically solved by nonlinear programming.

An intelligent connected vehicle (ICV) swarm system that includes N vehicles is considered. Based on the special properties of potential functions, a kinematic model describing the swarm performances is proposed, which allows all vehicles to enclose the tracking target and show both tracking and formation characteristics. Treating the performances as the desired constraints, the analytical form of constraint forces can be obtained inspired by the Udwadia-Kalaba approaches. A special approach of uncertainty decomposition to deal with uncertain interferences is proposed, and a switching-type robust control method is addressed for each vehicle agent in the swarm system. The features and validity of the addressed control are demonstrated in the numerical simulations.

The intelligent unmanned ground vehicle (UGV) motorcade system consisting of one leader and n − 1 followers is considered. The safety distance between the front and rear UGVs is treated as the control target. Since the safety distance constraint is a unilateral constraint, the state transformation is needed. Hence, a piecewise type conversion function is formulated to serve for the transformation of the original inequality constraint. The system equation is further expressed by the new state. We assume that the input of the leading UGV is known. Combined with the uncertainty evaluation, a class of collaborative controls for the following UGVs is proposed to deal with the uncertainty with unknown bound. The effectiveness of the designed control is verified by both Lyapunov stability theory and simulations. Both theoretical and simulation results illustrate that the longitudinal safety, stability and global behavior of the intelligent motorcade system are guaranteed.

In order to obtain a good understanding of mechanical behaviors of lithium-ion battery modules in electric vehicles, comprehensive experimental and numerical investigations were performed in the study. Mechanical indentation tests with different indentation heads, different loading directions and different impact speeds were performed on battery modules with prismatic cells. To mitigate thermal runaway, only fully discharged battery modules were used. The force-displacement responses and open circuit voltage were recorded and compared. It was found that the battery modules experienced different failure modes when subjected to mechanical abuse. Besides internal short circuit of cells, external short circuit from bus bar and vapor leakage of electrolyte were also found to deteriorate the mechanical and electrical integrity of the tested modules. Mechanical anisotropy and dynamic effect were found on the battery module.