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Intrusion Detection Systems (IDS), technically speaking, is to monitor the network, system, and operation status according to certain security policies, and try to find various attack attempts, attacks or attack results to ensure the confidentiality, integrity and availability of network system resources. Automotive intrusion detection systems can identify and alert by analyzing in-vehicle traffic and log when software applications or devices with malicious activity exist, or the in-vehicle network is tampered and injected. But unfortunately, automotive cybersecurity researchers hardly produce a comprehensive detection method due to the confidential nature of Controller Area Network (CAN) DBC format files, which is a standard long maintained by car manufacturers. In this paper, an enhanced intrusion detection method is proposed based on the double-decision-tree to classify different attack models for in-vehicle CAN network without the need to obtain complete DBC files.

An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.

Automatic Lane Change (ALC) function is an important step to promote the currently popular Advanced Driver Assistance Systems (ADAS) within a single lane. The key issue for ALC is accurate steering angle and trajectory tracking during the lane changing process. In this paper, an MPC controller with a receding horizon is designed to track the desired trajectory. During the tracking process, other objectives such as safety and smoothness are considered. Considering of the practical mechanism and parameter uncertainties, an SMC controller is designed to track the target steering angle. For validation, a Hardware-in-the-Loop (HIL) experiment platform is established, and experiments of different control algorithms under different conditions are carried out successively. Comparisons of the experiment results of MPC+SMC and PID+SMC schemes indicate that both the trajectory error and the steering angle error of the former combination are smaller.

Radar is playing more and important role in multiple object detection and tracking system due to the fact that Radar can not only determine the velocity instantly but also it is less influenced by environment conditions. However, Radar faces the problem that it has many detection clutter，false alarms and detection results are easily affected by the reflected echoes of road boundary in traffic scenes. Besides this, With the increase of the number of targets and the number of effective echoes, the number of interconnection matrices increases exponentially in joint probability data association, which will seriously affect the real-time and accuracy of high-speed scene algorithms.in the tracking system. So, A method of using millimeter wave radar to detect and fit the boundary guardrail of high-speed road is proposed, and the fitting results are applied to the vehicle detection and tracking system to improve the tracking accuracy.

Tire forces and moments play an important role in vehicle dynamics and safety. X-by-wire chassis components including active suspension, electronic powered steering, by-wire braking, etc can take the tire forces as inputs to improve vehicle’s dynamic performance. In order to measure the accurate dynamic wheel load, most of the researches focused on the kinematic parameters such as body longitudinal and lateral acceleration, load transfer and etc. In this paper, the authors focus on the suspension system, avoiding the dependence on accurate mass and aerodynamics model of the whole vehicle. The geometry of the suspension is equated by the spatial parallel mechanism model (RSSR model), which improves the calculation speed while ensuring the accuracy. A suspension force observer is created, which contains parameters including spring damper compression length, push rod force, knuckle accelerations, etc., combing the kinematic and dynamic characteristic of the vehicle.

Based on the emergency lane change cases extracted from the China naturalistic driving data, the driving steering behavior divides into three phases: collision avoidance, lateral movement and steering stabilization. Using the steering primitive fitting by Gaussian function, the distribution of the duration time, the relationship between steering wheel rate and deflection were analyzed in three phases. It is shown that the steering behavior essentially is composed of steering primitives during the emergency lane-change. However, the combination of the steering primitives is different according to the specific steering constraints in three phases. In the collision avoidance phase, a single steering primitive with high peak is used for the fast steering; in the lateral movement and stabilization phase, a combination of two or even more steering primitives is built to a more accurate steering.

Driver behaviors provide abundant information and feedback for future Advanced Driver Assistance Systems (ADAS). Driver’s eye and head may present some typical movement patterns before executing driving maneuvers. It is possible to use driver’s head and eye movement information for predicting driver intention. Therefore, to determine the most important features related to driver intention has attracted widespread research interests. In this paper, a method to analyze the correlation between driver’s visual features and driver intention is proposed, aiming to determine the most representative features for driver intention prediction. Firstly, naturalistic driving experiment is conducted to collect driver’s videos during executing lane keeping and lane change maneuvers. Then, driver’s head and face visual features are extracted from those videos. By using boxplot and independent samples T-test, features which have significant correlation with driver intention are found.

In this paper, a linear oscillatory actuator (LOA) with moving magnets used in active engine mount is modeled and theoretically analyzed considering its performance decline at high temperature. Firstly, a finite element model (FEM) of the LOA with moving magnets is established. The actuator force is decomposed to ampere force and cogging force through formation mechanism analysis. By using the FEM, ampere forces and cogging forces of the LOA with moving magnets under different current loads and different mover positions are calculated. The FEM and calculation method are validated by bench level test. The voice coil constant and cogging coefficient at normal temperature are identified, which indicates the actuator force is a linear model related to the current and the mover position.

Millimeter-wave automotive radars can prevent traffic accidents and save human lives as they can detect vehicles and pedestrians even in night and in bad weather. Various types of automotive radars operating at 24 and 77 GHz bands are developed for various applications, like adaptive cruise control, blind-spot detection and lane change assistance. In each year, millions of millimeter-wave radar are sold worldwide. Millimeter-wave radar is composed of radar hardware and radar signal processing software, which detects the targets among noise, measures the distance, longitudinal speed and the azimuth angle of the targets, tracks the targets continuously, and controls the ego vehicle to brake or accelerate. Performance of the radar signal processing software is closely related with the radar hardware properties and radar measurement conditions.

Two control strategies, safety preferred control and master cylinder oscillation control, were designed for anti-lock braking on a novel integrated-electro-hydraulic braking system (I-EHB) which has only four solenoid valves in its innovative hydraulic control unit (HCU) instead of eight in a traditional one. The main idea of safety preferred control is to reduce the hydraulic pressure provided by the motor in the master cylinder whenever a wheel tends to be locking even if some of the other wheels may need more braking torque. In contrast, regarding master cylinder oscillation control, a sinusoidal signal is given to the motor making the hydraulic pressure in the master cylinder oscillate in certain frequency and amplitude. Hardware-in-the-loop simulations were conducted to verify the effectiveness of the two control strategies mentioned above and to evaluate them.

Validation is one of the main challenges in development of automated driving systems (ADS). Due to the complexity of these systems and the various influence factors on their functional safety, current testcase generation methods can hardly guarantee the completeness and effectivity of the validation on system level. Separate validation of system components is a way to make system approval possible. In this paper, an approach is presented to generate deductively testcases for the validation of the environment perception sensors, which are the most essential components of ADS. This approach is originated from the model-based testing method, which is commonly used to validate software-based systems and extended by considering various external influence factors as follows: By modeling and analyzing applications in ADS, application oriented usecases of perception sensors are first derived.

For balancing Li-ion battery cells connected in series and effectively improving the consistency of the cells, a bi-directional equalization system based on fly-back transformer is proposed. Unlike the passive equalization technology using a resistor or active equalization with expensive DC-DC converter for the balancing among the cells, this equalization circuit consists of the fly-back transformer and RCD circuit, which can easily and cheaply realize the energy transfer between the whole battery module and the cells, and thus achieving bidirectional equalization. In this system, both the primary side and the secondary side of multi-winding transformer are connected to a MOSFET. All MOSFETs are controlled by the PWM signal. The control timing and duty ratio of the PWM control signal are determined through the simulation analysis. Meanwhile, an RCD circuit is applied at the primary side of multi-winding transformer for buffering the peak voltage caused by leakage inductance.

Vision based driving environment perception is current research hotspot in automatic driving field, which has made great progress due to the continuous breakthroughs in the research of deep neural network. As is well known, deep neural network has won tremendous successes in a wide variety of image recognition tasks, such as pedestrian detection and vehicle identification, which have accomplished the commercialization successfully in intelligent monitor system. Nevertheless, driving environment perception has a higher request for the generalization performance of deep neural network, which needs further studies on its design and training methods. In this paper, we presented a new boosted deep neural network in order to improve its generalization performance and meanwhile keep computational budget constant. Above all, the most representative methods to improve the generalization performance of deep neural network were introduced.

Brake judder severely affects the riding comfort and safety of vehicle. For the brake corner system, a rigid-flexible coupling model is established based on ADAMS. In the model, brake pads, caliper, anchor and knuckle are flexible bodies, and the contacts between pads and disc and the contacts between pads and caliper are defined in detail. Meanwhile, the vibration acceleration of the brake corner components and the contact forces between disc and pads are used as evaluation index and the evaluation system of brake judder are improved. The analysis results show that the novel model and evaluation system can be used to predict brake judder effectively.

The prevention and control of brake judder and its various negative effects has been a key target of vehicle production. One of the effects is the steering wheel vibration during vehicle braking. Experimental and theoretical investigation into “steering wheel vibration due to brake judder” is extensively presented in this paper. The vehicle road test is carried out under controlled braking conditions. During the test, the accelerations of brake caliper assembly, suspension low and upper control arm, steering arm, tie rod and steering wheel, left and right wheel rotary speed, are measured by a multi-channel data acquisition system. The data processing focuses on order tracking analysis and transfer path analysis to work out the related resonant components. A disc brake assembly, with deliberately designed disc thickness variation and surface run-out combinations, is tested on a brake dynamometer.

Brake judder affects vehicle safety and comfort, making it a key area of research in brake NVH. Transfer path analysis is effective for analyzing and reducing brake judder. However, current studies mainly focus on passenger cars, with limited investigation into commercial vehicles. The complex chassis structures of commercial vehicles involve multiple transfer paths, resulting in extensive data and testing challenges. This hinders the analysis and suppression of brake judder using transfer path analysis. In this study, we propose a simulation-based method to investigate brake judder transfer paths in commercial vehicles. Firstly, road tests were conducted to investigate the brake judder of commercial vehicles. Time-domain analysis, order characteristics analysis, and transfer function analysis between components were performed.

BBW (Brake-by-wire) can increase the vehicle safety performance due to high control accuracy and fast response speed. As one solution of BBW, the novel Integrated-electro-hydraulic brake system (I-EHB) is proposed, which consists of electro-hydraulic booster and hydraulic pressure control unit. The electro-hydraulic booster is activated by an electric motor that driving linear motion mechanism to directly produce the master cylinder pressure. With electro-hydraulic booster as an actuator, the hydraulic pressure control problem is a key issue. Most literatures deal with the pressure control issue based on the feedback pressure signal measured by pressure sensor. As far as the authors are aware, none of the proposed techniques takes into account the pressure sensor unequipped BBW. In this paper, there is no pressure feedback signal, but there is only position feedback signal measured by position sensor for control law design.

LiDAR and camera fusion have emerged as a promising approach for improving place recognition in robotics and autonomous vehicles. However, most existing approaches often treat sensors separately, overlooking the potential benefits of correlation between them. In this paper, we propose a Cross- Modality Module (CMM) to leverage the potential correlation of LiDAR and camera features for place recognition. Besides, to fully exploit potential of each modality, we propose a Local-Global Fusion Module to supplement global coarse-grained features with local fine-grained features. The experiment results on public datasets demonstrate that our approach effectively improves the average recall by 2.3%, reaching 98.7%, compared with simply stacking of LiDAR and camera.

The characteristics of three-way-catalyst during engine start process were investigated based on a simulated start/stop test system for HEV application. Although the catalyst has already reached its light-off temperature, the conversion efficiency is poor during engine start process due to the deviation of lambda from stoichiometric. The high concentration hydrocarbon emission spike can be stored by catalyst substrate temporarily, then it is released. This dynamic process decreases the conversion efficiency for the following exhaust hydrocarbon emission. When the initial temperature of catalyst substrate before engine start increased from 150°C to 400°C, the conversion efficiency for both the hydrocarbon and NO are increased.

As a newly designed hybrid transmission, DHT (Dedicated Hybrid Transmission) owns the advantages of compact structure, multi-modes and excellent comprehensive performance. Compared with the traditional add-on hybrid transmission with one single motor, DHT uses one independent generator for engine starting and speed adjusting which can be largely improve the driving performance in the mode changing process. Based on the series-parallel DHT with wet clutch for power coupling, this paper firstly analyses the power coupling clutch device functionalities from the power flow viewpoint under normal and limp home condition. And for the changing process from series to parallel mode, a clutch coordination control strategy is designed by combining generator fast speed adjusting with clutch accurately pressure controlling to fulfill the fast driver intension response and clutch protection.