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In the process of ABS control, the Anti-lock braking system (ABS) of the vehicle adjusts the wheel cylinder brake pressure through the hydraulic actuator so as to control the movement of the wheel. The high-speed on-off valve (HSV) is the key components of the Anti-lock braking system. HSV affects the performance of the hydraulic actuator and the valve response characteristics affects the Anti-lock braking system pressure response as well as braking effect. In this paper, the electromagnetic field theory and flow field theory of HSV are analyzed, and simulation analysis of electromagnetic field characteristics of HSV is done by ANSYS. Combined with the ANSYS analysis results, a precise physical model of HSV is constructed in AMESim. Meanwhile, the valve response characteristics are analyzed. Moreover, the influence of different wheel cylinder diameter and PWM carrier frequency on hydraulic braking force characteristics are analyzed.

Automatic lane change of intelligent vehicles is a complex process. Besides of safety, feelings of the driver and passengers during the lane change are also very important. In this paper, a lane change trajectory planner is designed to generate an ideal collision-free trajectory to satisfy the driver’s preference. Various lane changing modes, gentle lane change, general lane change, radical lane change and personalized lane change, are designed to meet the needs of different passengers on vehicles simultaneously. In this paper, the condition of the two-lane change is studied. One vehicle is in front of the ego vehicle at the same lane and one is at the rear of the ego vehicle at the target lane. A trajectory planning method is then established based on constant speed offset and sine curve, vehicle distances and speed difference, etc. The key factors which can reflect drivers’ lane change characteristics are then acquired.

With the development of autonomous vehicle technology, there is an increasing tendency toward the application of intelligent sensors in environment-perception system on autonomous vehicle to assist vehicle in intelligent decision making relevant to autonomous driving. As for environment-perception system, a good track management method serves as the foundation, while multi-target tracking and multi-sensor data fusion are recognized as the key. In this paper, a track management method is proposed to deal with multi-target tracking based on the target-level data of multisource environmental sensors for autonomous vehicle. The track management includes four procedures as following: track initiation; point-track association; track update; track deletion. A modified fast algorithm for data association is applied in the point-track association procedure. Afterwards Kalman filter is implemented to update the track information of target. The algorithm has got through a simulation test.

Millimeter wave automotive radar is one of the most important sensors in the Advanced Driver Assistance System (ADAS) and autonomous driving system, which detects the target vehicles around the ego vehicle via processing transmitted and echo signals. However, the sampling rate of classical radar signal processing methods based on Nyquist sampling theorem is too high and the resolution of range, velocity and azimuth can’t meet the requirement of highly autonomous driving, especially azimuth. In spatial domain, targets are sparse distribution in the detection range of automotive radar. To solve these problems, the algorithm for targets location based on compressed sensing for automotive radar is proposed in this paper. Besides, the feasibility of the algorithm is verified through the simulation experiments of traffic scene. The range-doppler-azimuth model can be used to estimate the distance, velocity and azimuth of the target accurately.

Target detection is essential to the advanced driving assistance system (ADAS) and automatic driving. And the data fusion of millimeter wave radar and camera could provide more accurate and complete information of targets and enhance the environmental perception performance. In this paper, a method of vehicle and pedestrian detection based on the data fusion of millimeter wave radar and camera is proposed to improve the target distance estimation accuracy. The first step is the targets data acquisition. A deep learning model called Single Shot MultiBox Detector (SSD) is utilized for targets detection in consecutive video frames captured by camera and further optimized for high real-time performance and accuracy. Secondly, the coordinate system of camera and radar are unified by coordinate transformation matrix. Then, the parallel Kalman filter is used to track the targets detected by radar and camera respectively.

Automotive radar is an important environment perception sensor for advance driving assistance system. It can detect objects around the vehicle with high accuracy and it works in all bad weathers. For traditional automotive radar, it cannot measure the objects’ height. Thus, a manhole cover on the road surface or a guideboard high above the road would be taken erroneously as a non-moving car. In such cases, the adaptive cruise system would decelerate or stop the vehicle erroneously and make the driver uncomfortable. A 3D automotive radar with two-dimensional electronic scanning can measure the targets’ height as well as the targets’ azimuth angle. This paper presents a 79 GHz ultra-wide band automotive 3D imaging radar. Due to the 4 GHz wide bandwidth, the range resolution of this radar can be as small as 3.75 cm.

In order to solve the problem that in the traditional trilateral positioning algorithm, the final positioning error is large when there is a certain error in the measured three-sided distance, a UWB positioning algorithm based on Back Propagation (BP) neural network is proposed. The algorithm utilizes the fast learning characteristic and the ability of approximating any non-linear mapping of neural network, and realizes the location of the mobile label through the TOA measurement value provided by the base station and the BP neural network. By comparing the traditional trilateral positioning algorithm, the BP neural network algorithm based on four distance inputs and the BP neural network algorithm based on four distance inputs with trilateral positioning coordinates, it can be seen that the positioning error of traditional trilateral positioning algorithm is 30 cm, and the positioning error of the positioning algorithm based on the BP neural network proposed in this paper is 10 cm.

Being one of the most simple and basic driving scenarios, highway scenario can be one of the first scenarios to achieve autonomous driving. Both car following (CF) and lane changing (LC) are the most basic and frequent maneuver during highway driving tasks, and therefore become two key issues to focus on in recent researches about autonomous vehicle (AV). Different from conventional CF and LC researches that attach much importance to the character, psychology, perception ability, and driving experience of human drivers, more timely and accurate reactions based on fast perception and communication technology as well as the automatic actuator are hypotheses for this research. Moreover, based on these hypotheses, a modified intelligent driver model (MIDM) is proposed for AVs’ following behavior to alleviate the fluctuations caused by lane changing behaviors.

Connected and autonomous vehicles are different from traditional vehicles. The communication between vehicles (V2V) or between vehicles and infrastructures (V2I) renders it possible to convey traffic information (e.g. signal timing or speed advisory) from signal controllers to vehicles as well as vehicles to vehicles in real time. Taking this advantage, this paper aims to developing an algorithm which enables the interconnected autonomous vehicles running efficiently on arterials. A set of driving rules determining random behavior and swarm behavior of autonomous vehicles is developed based on swarm intelligence theory. Under control of these rules, each autonomous vehicle follows the same rules, which make it select target vehicle from all the optimal individuals in detection zone according to characteristics of itself, then approach to the target by changing lane, following former car, or accelerating.

After obtaining the optimal trajectory through the lane change decision and trajectory planning, the last key technology for the automatic lane change assist system is to carry out the precise and rapid steering actuation according to the front wheel angle demand. Therefore, an automatic lane change system model including a BLDCM (brushless DC motor) model, a steering system model and a vehicle dynamics model is first established in this paper. Electromagnetic characteristics of the motor, the moment of the inertia and viscous friction etc. are considered in these models. Then, a SMC (Sliding Mode Control) algorithm for the steering system is designed to follow the steering angle input. The control torque of the steering motor is obtained through the system model according to steering angle demand. After that, the control current is calculated considering of electromagnetic characteristics of the BLDCM. Debugging and optimization of the control algorithm are done through simulations.

The automatic lane change assist system is an intelligent driving assistance technology oriented to traffic safety, which requires trajectory planning of the lane change maneuver based on the lane change decision. A typical scene of lane change for overtaking is selected, where the front vehicle in the same lane and the rear vehicle in the left lane are deemed to be potential dangerous vehicles through the lane change. Lane change trajectory equation is first established according to the general law of steering wheel angle through lane changes. Based on the relative position, velocity and acceleration information of the dangerous vehicles and the lane change vehicle, motions of these surrounding dangerous vehicles are predicted. At the same time, a multi-objective optimization function is established based on the relative longitudinal safety boundary. The objectives are the minimum safety distance, the lane change time and the front wheel angle.

Vehicle and pedestrian detection technology is the most important part of advanced driving assistance system (ADAS) and automatic driving. The fusion of millimeter wave radar and camera is an important trend to enhance the environmental perception performance. In this paper, we propose a method of vehicle and pedestrian detection based on millimeter wave radar and camera. Moreover, the proposed method complete the detection of vehicle and pedestrian based on dynamic region generated by the radar data and sliding window. First, the radar target information is mapped to the image by means of coordinate transformation. Then by analyzing the scene, we obtain the sliding windows. Next, the sliding windows are detected by HOG features and SVM classifier in a rough detect. Then using the match function to confirm the target. Finally detecting the windows in a precision detection and merging the detecting windows. The target detection process is carried out in the following three steps.

In view of the problem of low-frequency (less than 10Hz, such as 0.5Hz, 1.15Hz, 8Hz in this paper) longitudinal vibration exists in a pure electric vehicle, modeling methods of drive-line torsion vibration system are conducted. Firstly, dynamometer test is performed, signals of motor speed and seat rail acceleration are obtained, the frequency characteristics of flutter is determined using the order analysis and time frequency analysis. Then four types of modeling and analysis are investigated facing the drive-line torsion vibration problem, including single model without electromagnetic stiffness, branch model without electromagnetic stiffness, single model considering electromagnetic stiffness and branch model considering electromagnetic stiffness. The results show that, modeling taking into account the electromagnetic stiffness and branches can reflect more low-frequency characteristics helps to reveal the low-frequency longitudinal flutter of the researched electric vehicle.

In order to reduce high-frequency harmonic noise produced by the blower in the auxiliary system of a fuel cell vehicle (FCV), a narrowband active noise control (ANC) method instead of conventional passive mufflers is adopted since the blower demands clean air condition and expects good acoustic performance. However, in ANC practical applications, the frequency difference between reference signal and actual primary signal, i.e., frequency mismatch (FM), can significantly degrade the high-frequency performance of narrowband ANC system. In this paper, a new narrowband ANC system is proposed to compensate for the performance degeneration due to the existence of FM and improve noise reduction at high frequencies. The proposed system consists of two parts: the Filtered Error Least Mean Square (FELMS) algorithm filtering the primary signals at wide frequency range other than those at the targeted frequencies, and the FM removal algorithm proposed by Yegui Xiao.

To accurately and efficiently predict the temperature fields inside a lithium-ion battery is key technology for the enhancement of battery thermal management and the improvement of battery performances. The dimensional analysis method is applied to derive similarity criterions and the similarity coefficients of battery interior temperature fields, based on the governing partial differential equations describing the three dimensional transient temperature field. To verify the correctness of similarity criterions and the similarity coefficients, 3D finite element models of battery temperature field are established with a prototype and scale model, on the assumption that the battery cell has single-layer structure and multi-layers structure separately. The simulation results show that the similarity criterions and the similarity coefficients are correct.

The Forming limit diagram (FLD) is a powerful tool for describing the formability of sheet materials in the automobile industry, which provides fundamental data for die design and Finite Element (FE) simulation. However, traditional FLD testing is typically conducted at quasi-static strain rates from 0.001/s to 0.01/s, which are much lower than the industrial stamping process with strain rates about 1-10/s. In this research, FLDs at various punch speeds (from 1mm/s to 100mm/s or 120mm/s) were obtained for three kinds of AHSS, Quenched and Partitioned steel, Dual Phase 980 and Dual Phase 590 and three kinds of conventional steels, Low Alloy High Strength steel, Bake Hardening steel and IF steel. The results show that FLDs at a typical industrial stamping speed (100mm/s or 120mm/s) are considerably lower than the quasi-static test speed for the Advanced High Strength Steels (AHSS).

Torque Vectoring Control for distributed drive electric vehicle is studied. A handling improvement algorithm for normal cornering maneuvers is proposed based on state variable feedback control: Yaw rate feedback together with steer angle feedforward is employed to improve transient response and steady gain of the yaw rate, respectively. According to the feedback coefficient's influence on the transient response, an optimization function is proposed to obtain optimum feedback coefficients under different speeds. After maximum feedforward coefficients under different speeds are obtained from the constraint of the motor exterior characteristic, final feedforward coefficients are calculated according to an optimal steering characteristic. A torque distribution algorithm is presented to help the driver to speed up during the direct yaw moment control.

Air purifier has been prevalently used in the passenger vehicle cabins to reduce in-cabin UltraFine Particle (UFP) concentration. In this study, Computational Fluid Dynamics (CFD) was applied to simulate the in-cabin UFP transport and distribution under different ventilation modes with different characteristics of the air purifier. Ventilation settings, air purifier settings, and air purifier location were identified as the important factors determining the in-cabin UFP distribution and transport. Downward ventilation airflow direction and smaller ventilation air velocity can be considered by the drivers for a lower in-cabin UFP concentration. Upward airflow direction from the air purifier's inlet and larger air velocity were recommended since it led up to 50% in-cabin UFP reduction. Air purifier installed at middle ceiling of the cabin develops the most efficient airflow for UFP removal.

Similar laser welded blanks with same material and same gauge have been extensive applied in automobile body for improving the material utilization and extending maximum coil size. It is known that, for TWBs with dissimilar material and thicknesses, the difference of material properties and/or thickness of the welded blanks, change of the material properties in the weld seam and heat-affected zones (HAZ) as well as location and orientation of the weld seam are reasons for reduced formability. However, the plastic deformation capacity of TWBs is reduced even when the material and thickness are the same. The aim of this paper is to evaluate the deformation behaviors of similar laser welded joints. Uniaxial tensile of five laser welded joints, with 90°,60°,45°,30°and 0°weld orientations, were tested by using optical measurement-DIC (Digital Image Correlation). Strain /strain ratio distribution and evolution of each joint was analyzed and compared with base material.

For achieving vehicle light weighting, the motion deviation is calculated for substitution of PMMA glazing for inorganic glass. In this paper, a test method is proposed to measure and calculate the motion deviation of the dual-curvature glass. To simulate the dual-curvature glass, the torus surface is fitted with least square method according to the window frame data, which are measured by Coordinate Measuring Machine. By using this method, the motion deviation of PMMA glazing and inorganic glass can be calculated, which can not only validate the effectiveness of motion simulation, but also compare the performances. The results demonstrate that the performance of PMMA glazing is better than that of inorganic glass and the simulation results is validated.