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Vehicle hood styling has significant influence on headform kinematics in assessment tests of pedestrian impact protection performance. Pedestrian headform kinematics on vehicle front-end models with different hood styling characteristics is analyzed based on finite element modeling. More elevated feature lines near hood boundary and the following continuous hood surface towards fender will result in a different headform motion. It can lead to larger deformation space, more rotation and earlier rebound of the headform impactor, which will benefit the head impact protection performance. In addition, hood geometry characteristics such as hood angle and curvature have effects on structural stiffness. Therefore, inclusion of considerations on pedestrian head protection into the vehicle hood styling design stage may lead to a more effective and efficient engineering design process on headform impact analysis.

The conventional hood with single material and stiffener structural form conceals some limitations on pedestrian protection and lightweight, not satisfying the requirements of structural strength, pedestrian protection and lightweight contradictory with each other at the same time. In this paper, a novel type hood is proposed to develop sandwich structure using architected cellular material with negative Poisson's ratio (NPR) configuration based on the decoupling thought of structural strength and energy absorption. Core-layer aluminum alloy material with NPR is used to meet the requirement of impact energy absorption, inner and outer skin using carbon fiber is selected to achieve high structural stiffness needed. This paper starts from the relations between geometric parameters of core-layer architected cellular material and mechanical properties, on this basis, the optimal geometric parameters can be expected using the multiobjective optimization method.

High-precision and real-time ego-motion estimation is vital for autonomous vehicle. There is a lot GPS-denied maneuver such as underground parking lot in urban areas. Therefore, the localization system relying solely on GPS cannot meets the requirements. Recently, lidar odometry and visual odometry have been introduced into localization systems to overcome the problem of missing GPS signals. Compared with visual odometry, lidar odometry is not susceptible to light, which is widely applied in weak-light environments. Besides, the autonomous parking is highly dependent on the geometric information around the vehicle, which makes building map of surroundings essential for autonomous vehicle. We propose a lidar inertial odometry and mapping. By sensor fusion, we compensate for the drawback of applying a single sensor, allowing the system to provide a more accurate estimate.

Intelligent driving, aimed for collision avoidance and self-navigation, is mainly based on environmental sensing via radar, lidar and/or camera. While each of the sensors has its own unique pros and cons, camera is especially good at object detection, recognition and tracking. However, unpredictable environmental illumination can potentially cause misdetection or false detection. To investigate the influence of illumination conditions on detection algorithms, we reproduced various illumination intensities in a photo-realistic virtual world, which leverages recent progress in computer graphics, and verified vehicle detection effect there. In the virtual world, the environmental illumination is controlled precisely from low to high to simulate different illumination conditions in the driving scenarios (with relative luminous intensity from 0.01 to 400). Sedan cars with different colors are modelled in the virtual world and used for detection task.

In the performance evaluating of Electronic Brake System, conventional test methods have some inconvenience in existence. For example, the fixing of pressure sensors and wheel speed sensors is restrained by the installation position, and the precision of measuring is prone to be affected by the environment conditions. Since Electronic Brake System is featured by CAN (Controller Area Network) communication, special testing instrument can be connected with CAN bus, monitoring signals transmitting on the bus. This paper outlines the results of the study performed to analyze the application of CAN communication in the way of performance evaluation of Electronic Braking System.

In order to solve the abnormal vibration of a light bus, order tracking analysis of finite element simulation and road test was made to identify the vibration source, finding that the rotation angular frequency of the wheels and the first two natural frequency of the body structure overlaps, resonance occurring which lead to increased vibration. To stagger the first two natural frequency and excitation frequency of the body, thickness of sheet metal and skeleton of the body-in-white were chosen as the design variables, rise of the first two natural frequency of the body-in-white as the optimization objective, optimal design and sensitivity analysis of the body-in-white was carried out with the modal analysis theory. Combining with the modal sensitivity and mass sensitivity of sheet metal and skeleton, the optimum design was achieved and tests analysis was conducted.

In-cylinder pressure sensor, which provides the means for precise combustion control to achieve improved fuel economy, lower emissions, higher comfort, additional diagnostic functions etc., is becoming a necessity in future diesel engines, especially for chemical-kinetics dominated PCCI (Premixed Charge Compression Ignition) or LTC (Low Temperature Combustion) engines. In this paper, new control strategy is investigated to utilize in-cylinder pressure information into engine start process, in order to guarantee the success of engine start and in the meantime prevent penalty of fuel economy or pollutant emissions due to excessive fuel injection. An engine start acceleration model is established to analyze the engine start process. “In-cylinder Combustion Analysis Tool” (i-CAT), is used to acquire and process the in-cylinder pressure data and deliver the combustion indices to ECU (Engine Control Unit). Feedback control is accomplished in ECU based on this information.

The paper presents a new electromechanical brake system for vehicles using magnetorheological fluid. The brake system designed for the electric vehicle has some advantages over the conventional brake system. The brake system is made up of a brake disk, shells, magnetorheological fluid (MRF) and the electromagnets. The brake disk is immersed in the MRF whose yield stress changes as the applied magnetic field. The braking torque of this system can be linearly adjusted by the current in just a few milliseconds without the conventional vacuum booster. This system has a quick response and precise control performance with a low hysteresis. Besides, the system has adopted the original complicated structure to save space and cost. In this paper, the configuration of MRF brake types is described. The braking torques of the MRF brakes is derived based on the MRF theoretical model which is firstly raised. Some braking simulation based on the theoretical model is also shown.

This paper studies a multi-objective optimization design of interior noise for an automotive body. An acoustic-structure coupled model with materials and properties was established to predict the interior noise based on a passenger car. Moreover, three kinds of approximation models related damping thickness and the root mean square of the driver’s ear sound pressure level were established through Latin hypercube method and the corresponding experiments. The prediction accuracy was analyzed and compared for the approximate response surface model, Kriging model and Radial Basis Function neural network model. On this basis, multi-objective optimization of the vehicle interior noise was conducted by using NSGA-II. According to the optimization results, the damping composite structure was applied on the car body structure. Then, the comparison of sound pressure level response at driver’s ear location before and after optimization was performed at speed of 60 km/h on a smooth road.

In order to improve drivers’ acceptance to advanced driver assistance systems (ADAS) with better adaptation, drivers’ driving behavior should play key role in the design of control strategy. Adaptive cruise control systems (ACC) have many factors that can be influenced by different driving behavior. It is important to recognize drivers’ driving behavior and take human-like parameters to the adaptive cruise control systems to assist different drivers effectively via their driving characteristics. The paper proposed a method to recognize drivers’ behavior and intention based on Gaussian Mixture Model. By means of a fuzzy PID control method, a personalized ACC control strategy was designed for different kinds of drivers to improve the adaptabilities of the systems. Several typical testing scenarios of longitudinal case were created with a host vehicle and a traffic vehicle.

A fault tolerant control (FTC) approach based on reconfigurable control allocation for four-wheel independently driven and steered (4WID/4WIS) electric vehicles against driving motor failures is proposed in order to improve vehicle safety, performance and maneuverability after the driving motor failures. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle driving condition, detects and diagnoses actuator failures; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using model predictive control method; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels aiming at minimizing the total tire usage. The FTC approach is based on the reconfigurable control allocation which reallocates the generalized forces/moments among healthy actuators once the actuator failures is detected.

Lane detection and tracking play a key role in autonomous driving, not only in the LKA System but help estimate the pose of the vehicle. While there has been significant development in recent years, traditional outdoor SLAM algorithms still struggle to provide reliable information in challenging dynamic environments such as lack of roadside landscape or surrounding vehicles at almost the same speed or on the road in the woods. On the structured road, lane markings as static semantic features may provide a stable landmark assist in robust localization. As most of the current lane detection work mainly on separated images ignoring the relationship between adjacent frames, we propose a pixel-level lane tracking method for autonomous vehicles. In this paper, we introduce a deep network to detect and track lane features. The network has two parallel branches. One branch detects the lane position, while the other extracts the point description on a pixel level.

A low frequency vibration issue around 3.2 Hz occurs during a commercial heavy truck program development process, and it is linked to extremely uncomfortable driving and riding experiences. This work focuses on an analytical effort to resolve the issue by first building a full vehicle MBS (multi-body-system) model, and then carrying out vibration response analyses. The model validation is performed by using full vehicle testing in terms of structural modes and frequency response characteristics. In order to resolve the issue which is excited by tire non-uniformity, the influence of the cab suspension, frame modes, front leaf spring system and rear tandem suspension is analyzed. The root cause of the issue is found to be the poor isolation of the rear tandem suspension system. The analytical optimization effort establishes the resolution measure for the issue.

For the roll vibration problem of a Truck, a 4-DOF roll vibration model of its front suspension system was built. According to dynamics theory, the complex modal vibration modes of the model were all obtained. At the same time, the frequency response functions of frame roll angle acceleration, the relative dynamic load of wheel and the suspension dynamic deflection were respectively presented. Then their characteristics were respectively researched. In the process of characteristic analysis, a new system parameter was proposed, which is the space ratio of the space between suspensions of left and right sides and the wheel track of the front axle (space ratio in short). At last, the influence of system parameters on the vibration transmission property was also reserached, which included the natural frequency of the frame, the damping ratio, the stiffness ratio, the mass ratio, the rotational inertia ratio and the space ratio.

Aiming at the difficulty of sovling the stiffness calculation of taper-leaf spring with variable stiffness, a combined method was proposed, which combine superposition method and finite difference method. Then the calculation results of different differential segments were compared with experimental results. The compared results show that the proposed method is effective and simple. So it has some practical significance in designing the taper-leaf spring. In addition, based on the stiffness test of the taper-leaf spring, the proper adjustments to the correction factor of the single parabolic leaf spring stiffness formula was recommended(ξ =0.92-0.96).

When a sunroof opens to let in fresh air while driving, there might be several noise issues associated with it. The most common and painful one is the wind throb issue, which is nevertheless largely resolved by implementing a sufficiently high wind deflector along the front edge of the sunroof. However, with the wind throb suppressed, other sound quality issues might emerge. The most notable one is the hissing noise issue, which becomes increasingly objectionable with the increase of vehicle speed. This work looks into the impact of sunroof deflector on interior sound quality with the consideration of wind throb, hissing noise and booming noise in terms of psychoacoustic attributes that could be felt subjectively. The goal is to achieve a better understanding of the sound quality associated with the sunroof deflector design, and inspire a balanced design, potentially targeting the most NVH demanding customers in the premium vehicle segment.

Wind noise is one of the most influential NVH attributes that impact customer sensation of vehicle interior quietness. Among many factors that influence wind noise performance, the amount of dynamic door deflection under the pressure load due to fast movement of a vehicle plays a key roll. Excessive deflection could potentially lead to loss of sealing contact, causing aspiration leakage, which creates an effectual path through which the exterior aerodynamically induced noise propagates into the vehicle cabin. The dynamic door deflection can be predicted using CFD and CAE approaches which, in addition to modeling the structure correctly, require a correct pressure loading composed of external and internal pressure distributions. The determination of external pressure distributions can be fulfilled fairly straightforward by using commercial CFD codes such as Fluent, Star CCM+, Powerflow and others.

In the field of automatic driving, the combination of 3D LIDAR and inertial measurement unit (IMU) is a common sensor configuration scheme in laser point-cloud localization, high-precision map making and point-cloud target detection. So it is critical to calibrate LIDAR and IMU accurately. At present, due to the large volume and high cost of 3D LIDAR with high-line-number(Such as 64 lines or 128 lines), the configuration scheme of using multiple low-line-number 3D LIDARs appears in the automatic driving vehicle sensing system. However, the common calibration methods are not suitable for multi 3D LIDARs and IMU parameters calibration on autonomous vehicle, which have the disadvantages of cumbersome implementation and low accuracy. In this paper, a joint calibration test platform composed of dual LIDARs and IMU is assembled, and a method of precise automatic calibration based on GPS/RTK data is proposed.

Accurate tire pressure monitoring system (TPMS) is of great practical importance and the reliability and safety of its power supply module has great concern. The piezoelectric-based surface acoustic wave (SAW) sensor is considered to have great potential in this field because of its passive, wireless and small size advantages. This paper presents the application of passive and wireless SAW sensors for real-time tire condition monitoring. The pressure sensitive structure is optimized and a three-resonator structure is also designed sensing temperature and pressure. Furthermore, a fast detection system is developed to realize high-speed signal acquisition. At last, experiments are executed and the SAW temperature and pressure sensor property is measured.

In recent years, intelligent vehicles have become one of the major research topics in vehicle engineering and have created a new opportunity for the automotive industry. Simulation and real experiment are both essential to the development of intelligent vehicle technologies. Vehicle positioning systems, such as global positioning system (GPS), play an important role in intelligent vehicle development. The GPS model plays a major part in the development of intelligent vehicle simulation systems. Primarily focusing on application requirements of intelligent vehicle simulation platforms for GPS sensor modeling, considering the major factors affecting positioning accuracy in vehicle driving environments, this article establishes a new GPS model and algorithm based on the physical and functional characteristics of GPS. As the basis of this model system, a precise ephemeris model is established to obtain the coordinates of GPS satellites at any given time.