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SLAM (Simultaneous Localization and Mapping) plays a key role in autonomous driving. Recently, 4D Radar has attracted widespread attention because it breaks through the limitations of 3D millimeter wave radar and can simultaneously detect the distance, velocity, horizontal azimuth and elevation azimuth of the target with high resolution. However, there are few studies on 4D Radar in SLAM. In this paper, RI-FGO, a 4D Radar-Inertial SLAM method based on Factor Graph Optimization, is proposed. The RANSAC (Random Sample Consensus) method is used to eliminate the dynamic obstacle points from a single scan, and the ego-motion velocity is estimated from the static point cloud. A 4D Radar velocity factor is constructed in GTSAM to receive the estimated velocity in a single scan as a measurement and directly integrated into the factor graph. The 4D Radar point clouds of consecutive frames are matched as the odometry factor.

An electrochemical impedance spectroscopy battery model based on the porous electrode theory is used in the paper, which can comprehensively depict the internal state of the battery. The effect of battery key parameters (the radius of particle, electrochemical reaction rate constant, solid/electrolyte diffusion coefficient, conductivity) to the simulated impedance spectroscopy are discussed. Based on the EIS analysis, a lithium-ion battery optimized equivalent circuit model is built. The parameters in the equivalent circuit model have more clear physical meaning. The reliability of the optimized equivalent circuit model is verified by compared the model and experiments. The relationship between the external condition and internal resistance could be studied according to the optimized equivalent circuit model. Thus the internal process of the power battery is better understood.

Battery models are often applied to describe the dynamic characteristics of batteries and can be used to predict the state of the battery. Due to the process of charging and discharging, the battery heat generation will cause the inhomogeneity between inner battery temperature and surface temperature. In this paper, a novel battery impedance model, which takes the impact of the battery internal temperature gradient on battery impedance into account, is proposed to improve the battery model performance. Several experiments are designed and conducted for pouch typed battery to investigate the electrochemical impedance spectroscopy (EIS) characteristics with the artificial temperature gradient (using a heating plate). Experimental results indicate that the battery internal temperature gradient will influence battery EIS regularly.

Autonomous driving related technologies have become a hot topic in academia and industry. Planning control is one of the core technologies of autonomous driving, which is conducive to vehicles safe and efficient driving. This paper proposes a novel optimal speed control algorithm, which considers the power system's energy consumption, the speed limit on the road, and the safe distance of the vehicle in front. An optimal speed control model of “From battery to wheel” energy consumption is established by constructing a performance index function based on the best-fitting formula of motor power, motor speed and torque. Based on the optimal control principle, the fourth-order ordinary differential equation of the speed control model is established, based on the indirect adjoining approach, the speed control model under the restriction of the road speed limit and safe distance of the preceding vehicle is derived and the analytical expression is obtained.

As one of the key technologies in autonomous driving, the lateral planning module guides the lateral movement during the driving process. An integrated lateral planning module should consider the non-holonomic constraints of a vehicle, the optimization of the generated trajectory and the applicability to various scenarios. However, the current lateral planning methods can only meet parts of these requirements. In order to satisfy all the performance requirements above, a novel Potential Field (PF) based lateral planning method is proposed in this paper. Firstly, a PF model is built to describe the potential risk of the traffic entities, including the obstacles, road boundaries and lines. The potential fields of these traffic entities are determined by their properties and the traffic regulations. Secondly, the planning algorithm is presented, which comprises three modules: state prediction, state search and trajectory generation.

The hydrogen supply integrated subsystem is an important part of the proton exchange membrane fuel cell system. In the multi-stack fuel cell system, the optimal design and integration of the hydrogen supply subsystem have great influence on the whole system structure. In this paper, a fuel cell hydrogen integration subsystem with two hydrogen cycle structures is established based on an optimized split-stack approach. Firstly, the matching of hydrogen subsystem is carried out on the basis of multi-stack fuel cell optimization. Then, the structure of the gas buffering and distribution device and the gas circulation device is optimized considering the gas circulation and the diversity of the equipment, and two solutions are proposed: the separate circulation structure (Structure I) and the common circulation structure (Structure II). Finally, the multi-stack fuel cell system is built by MATLAB/Simulink software and simulated under the condition of step and C-WTVC.

To solve the problem of serious roller wear and improve the smoothness of the sliding door motion process, the rigid-flexible coupling multi-body model of the vehicle sliding door was built in ADAMS. Force boundary conditions of the model were determined to meet the speed requirement of monitoring point and time requirement of door opening-closing process according to the bench test specification. The results of dynamic simulation agreed well with that of test so the practicability and credibility of the model was verified. In the optimization of the ride comfort of the sliding door, two different schemes were proposed. The one was to optimize the position of hinge pivots and the other was to optimize the structural parameters of the middle guide. The impact load of lead roller on middle guide, the curvature of the motion trajectory and angular acceleration of the sliding door centroid were taken as optimization objectives.

The optimization of speed holds critical significance for pure electric vehicles. In multi-intersection scenarios, the determination of terminal velocity plays a crucial role in addressing the complexities of the speed optimization problem. However, prevailing methodologies documented in the literature predominantly adhere to a fixed speed constraint derived from traffic light regulations, serving as the primary basis for the terminal velocity constraint. Nevertheless, this strategy can result in unnecessary acceleration and deceleration maneuvers, consequently leading to an undesirable escalation in energy consumption. To mitigate these issues and attain an optimal terminal velocity, this paper proposes an innovative speed optimization method that incorporates a terminal-velocity heuristic. Firstly, a traffic light state model is established to determine the speed range required to avoid coming to a stop at signalized intersections.

As a prerequisite for energy management of hybrid vehicles, the results of speed prediction can optimize the performance of vehicles and improve fuel efficiency. Energy management strategies are usually developed based on standard driving cycles, which are too generalized to show the variability of driving conditions in different time and locations. Therefore, this paper constructs a representative driving cycle based on driving data of the corresponding time and location, used as historical information for prediction. We propose a method to construct the driving cycle based on Markov chain theory before constructing the prediction model. In this paper, multiple prediction methods are compared with traditional parametric methods. The difference in prediction accuracy between multiple prediction methods under the single time scale and multiple time scale were compared, which further verified the advantages of the speed prediction method based on Markov chain theory.

On the study of reducing the disturbance on driver’s attention induced by low frequency vehicle interior stationary noise, a subjective evaluation is firstly carried out by means of rank rating method which introduces Distraction Level (DL) as evaluation index. A visual-finger response test is developed to help evaluating members better recognize the Distraction Level during the evaluation. A non-linear back propagation artificial neural network (BPANN) is then modeled for the prediction of subjective Distraction Level, in which linear sound pressure RMS amplitudes of five Critical Band Rates (CBRs) from 20 to 500Hz are selected as inputs of the model. These inputs comprise an input vector of BPANN. Furthermore, active noise equalization (ANE) on DL is realized based on Filtered-x Least Mean Square (FxLMS) algorithm that controls the gain coefficients of inputs of trained BPANN.

The efficiency and durability of fuel cells are affected by internal water content. Therefore, the active control of humidity is of great significance for vehicle fuel cells, especially for self-humidifying fuel cell systems. To realize fuel cell internal humidity active control, it is necessary to collect the humidity information of stack in real time, so as to carry out feedback control. However, humidity sensor has the characteristics of high cost and low durability, so it is more practical to get the feedback value of humidity by using state estimation method for high-power commercial fuel cell system such as vehicle fuel cell. However, humidity estimation is often affected by other physical or chemical dynamic processes, such as oxygen transportation and response process of electrical appliances. In order to weaken the influence of other physical or chemical dynamic processes on humidity estimation, this paper proposes an adaptive sliding mode Kalman observer (ASMK) algorithm.

Manufacturers have been encouraged to accommodate advanced downsizing technologies such as the Variable Displacement Engine (VDE) to satisfy commercial demands of comfort and stringent fuel economy. Particularly, Active control engine mounts (ACMs) notably contribute to ensuring superior effectiveness in vibration attenuation. This paper incorporates a PID controller into the active control engine mount system to attenuate the transmitted force to the body. Furthermore, integrated time absolute error (ITAE) of the transmitted force is introduced to serve as the control goal for searching better PID parameters. Then the particle swarm optimization (PSO) algorithm is adopted for the first time to optimize the PID parameters in the ACM system. Simulation results are presented for searching optimal PID parameters. In the end, experimental validation is conducted to verify the optimized PID controller.

The turbocharger air intake noise during transient conditions like wide open throttle and tip-in/out affects the passenger ride comfort. This paper aims to study an optimized design of multi-chamber perforated resonators to attenuate this noise. The noise produced by a turbocharger in a test vehicle has been measured to find out the noise spectral characteristics which can be used to design the acoustic targets including the amplitude and frequency range of transmission loss (TL). The structural parameters of the resonators are optimized based on genetic algorithm (GA) and two-dimensional prediction theory of the resonator TL. The optimized resonators are installed on the test vehicle to verify the actual noise reduction effect. The results suggest that the broadband noise has been eliminated, and subjective feelings are greatly improved.

With the growing prosperity of the long-distance freight and urban logistics industry, the demand for cargo trucks is gradually increasing. The connecting bracket is the critical connecting part of the truck chassis, which bears the load transmitted by the road excitation and reduces the damage to the frame caused by the load. However, the occurrence of rough road conditions is inevitable in heavy-duty transportation. In this paper, road durability tests and fatigue life analysis are carried out on the original structure to ensure the safety of the vehicle. Based on the known boundary and load constraints, a lightweight and high-performance structure is obtained through size optimization, as the original structure cannot meet the performance requirements. Firstly, the road test was conducted on the truck where the original bracket structure is located.

Gradient based topology optimization method is difficult used to optimization of crashworthiness structures due to the expensive computational cost of sensitivity analysis and complex nonlinear behaviors (geometric nonlinearity, material nonlinearity and contact nonlinearity) of structures during a collision. Equivalent static loads (ESLs) method is one of the methods for nonlinear dynamic response optimization. However, this method ignores the material nonlinearity. Thus this paper proposes an improved topology optimization method for crashworthiness structure based on a modified ESLs method. A new calculation of ESLs considering material nonlinearity is proposed. The improved ESLs method is employed to transform the nonlinear dynamic response optimization into a nonlinear static response optimization with multiple load cases. Each element in the design domain is assigned with a design variable.

In order to improve the robustness and stability of autonomous vehicle at high speed, a path tracking approach which combines front steering and differential braking is investigated in this paper. A bicycle model with 3-DOFs is established and a linear time-varying predictive model using front steering as its control input can be derived. Based on model predictive theory, the path tracking issue using linear time-varying model predictive control can be transformed into an online quadratic programming problem with constraints. The expected front steering angle can be obtained from online moving optimization. Then the direct yawing control is adopted to treat two types of differential braking control. The first one investigates steady-state gain of yaw rate in linear 2-DOFs vehicle model, and designs a stable differential braking controller which is based on reference yaw rate.

Active engine mount (AEM) is an effective approach which can optimize the noise, vibration and harshness (NVH) performance of vehicles. The filtered-x-least-mean-squares (FxLMS) algorithm is widely applicated for vibration attenuation in AEMs. However, the performance of FxLMS algorithm can be deteriorated without an accurate secondary path estimation. First, this paper models the secondary path using finite impulse response (FIR) model, infinite impulse response (IIR) model and back propagation (BP) neural network model and the model errors of which are compared to determine the most accurate and robust modeling method. After that, the influence of operation frequency on accuracy of the secondary path model is analyzed through simulation approach. Then, the impact of reference signal mismatch on the control effect is demonstrated to study the robustness of FxLMS algorithm.

A composite steering control strategy, which combines four-wheel steering (4WS) and differential steering, is proposed in this paper, to optimize steering maneuverability in the conditions where the vehicle speed is below 15 Km/h, mainly for U-turning and parking conditions. A dynamic model is developed for the steering system and the tire system. Taking different steering wheel inputs into consideration, a 4WS control strategy proportional to the front wheel steering angle is quoted to improve the steering maneuverability in the low speed conditions and guarantee the manipulability by controlling the side slip of the vehicle. Based on the 4WS system, this paper explores the possibility of further improving the low-speed maneuverability of the vehicle through differential steering. And the differential steering control strategy is developed, including four hub-motor output modes. A composite steering controller is designed based on the 4WS-4WD electric vehicle platform.

Battery safety issues have severely limited the rapid development and popularization of electric vehicles. Harsh conditions such as high temperature accelerate the degradation of battery safety. To address this issue, a comprehensive analysis of the impact of high-temperature cyclic aging on lithium-ion battery safety is carried out. In the Accelerating Rate Calorimeter, lithium-ion batteries are performed on adiabatic thermal runaway tests and overcharge tests. Regardless of the fully-charged state or half-charged state, in the adiabatic thermal runaway process, high-temperature cyclic aging reduces the characteristic temperature, and the activation energy from the self-heating temperature to thermal runaway triggering temperature decreases. During the overcharge process, high-temperature cyclic aging increases the voltage plateau and the crest voltage before thermal runaway, and their corresponding charging temperature decreases.

Carbon fiber reinforced plastic (CFRP) composites have gained particular interests due to their high specific modulus, high strength, lightweight and resistance to environment. In the automotive industry, numerous studies have been ongoing to replace the metal components with CFRP for the purpose of weight saving. One of the significant benefits of CFRP laminates is the ability of tailoring fiber orientation and ply thickness to meet the acceptable level of structural performance with little waste of material capability. This study focused on the concurrent optimization of ply orientation and thickness for CFRP laminated engine hood, which was based on the gradient-based discrete material and thickness optimization (DMTO) method. Two manufactural constraints, namely contiguity and intermediate void constraints, were taken into account in the optimization problem to reduce the potential risk of cracking matrix of CFRP.