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This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

The driving behaviors of young drivers under the influence of anger are analyzed by driving simulator in this paper. A total of 12 subjects are enrolled during the experiment. Standardized videos are utilized to induce the driver's anger emotion. And the driver's electrocardiogram (ECG) signal is collected synchronously and compared before and after emotional trigger, which prove the validity of emotional trigger. Based on the result, the driver's driving performance under the straight road and the curve under normal state and angry state are compared and analyzed. The results of independent sample t-test show that there are significant differences in the running time of straight sections and the standard deviation of steering wheel angle in curves between normal and angry states. In conclusion, the longitudinal and lateral operation of drivers is unstable in angry state and the driver will be more destructive to the regular driving behavior.

The accuracy of tire forces directly affects the vehicle dynamics model precision and determines the ability of the model to develop the simulation platform or design the control strategy. In the high slip angle, due to the complex interactions at tire-road interfaces, the forces generated by the tires are high nonlinearity and uncertainty, which pose issues in calculating tire force accurately. This paper presents a hybrid physical and data-driven tire force calculation framework, which can satisfy the high nonlinearity and uncertainty condition, improve the model accuracy and effectively leverage prior knowledge of physical laws. The parameter identification for the physical tire model and the data-based compensation for the unknown errors between the physical tire model and actual tire force data are contained in this framework. First, the parameters in the selected combined-slip Burckhardt tire model are identified by the nonlinear least square method with tire test data.

Lane detection is one of the most important part in ADAS because various modules (i.e., LKAS, LDWS, etc.) need robust and precise lane position for ego vehicle and traffic participants localization to plan an optimal routine or make proper driving decisions. While most of the lane detection approaches heavily depend on tedious pre-processing and great amount of assumptions to get reasonable result, the robustness and efficiency are deteriorated. To address this problem, a novel framework is proposed in this paper to realize robust and real-time lane detection. This framework consists of two branches, where canny edge detection and Progressive Probabilistic Hough Transform (PPHT) are introduced in the first branch for efficient detection.

A high-precision steady state tire model is critical in the tire and vehicle matching research. For the moment, the popular Magic Formula model is an empirical model, which requires the pure and combined test data to identify the model parameters. Although MTS Flat-trac is an efficient tire test rig, the long test period and high test cost of a complete tire model tests for handling are yet to be solved. Therefore, it is necessary to explore a high accuracy method for predicting tire complex mechanical properties with as few test data as possible. In this study, a method for predicting tire combined slip characteristics from pure cornering and pure longitudinal test data has been investigated, and verified by comparing with the test data. Firstly, the prediction theory of UniTire model is introduced, and the formula for predicting combined slip characteristics based on constant friction coefficient is derived.

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

Active control of low-frequency engine order noise helps to improve the passenger’s sense of hearing, so it has become one of the hot topics in the automotive field. Depth improvement of active noise control (ANC) performance from the perspective of novel algorithms has attracted the attention of researchers. The conventional notch dual-channel filtered-x least mean square (NDFxLMS) algorithm shows acceptable noise reduction for the elimination of engine order noise. To further enhance the steady-state ANC effect, this paper proposed two new notch algorithms: the notch dual-channel filtered-x recursive least square (NDFxRLS) algorithm and the notch dual-channel affine projection (NDAP) algorithm. Vehicle simulation tests show that both the proposed algorithms, especially the NDFxRLS algorithm, have a satisfying performance for the cancellation of interior noise from the engine.

The Electronic Mechanical Braking (EMB) system, which offers advantages such as no liquid medium and complete decoupling, can meet the high-quality active braking and high-intensity regenerative braking demands proposed by intelligent vehicles and is considered one of the ideal platforms for future chassis. However, traditional control strategies with fixed clamping force tracking parameters struggle to maintain high-quality braking performance of EMB under variable braking requests, and the nonlinear friction between mechanical components also affects the accuracy of clamping force control. Therefore, this paper presents an adaptive clamping force control strategy for the EMB system, taking into account the resistance of nonlinear friction. First, an EMB model is established as the simulation and control object, which includes the motor model, transmission model, torque balance model, stiffness model, and friction model.

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.

A vehicle’s NVH performance has a significant impact on the user experience of the driver and passengers. About one-third of the vehicle complaints are related to NVH performance. As the core component of the vehicle, the drivetrain’s NVH characteristics have a significant impact on vehicle comfort. How to reliably and stably reproduce the specific condition of the whole vehicle through the test method, and obtain the highly consistent objective data for analyzing and improving the NVH characteristics of the drivetrain is of great significance in engineering. For this purpose, China Automotive Technology Research Center Co., Ltd. (CATARC) designed and built a new type drivetrain NVH test facility, which consists of five dynamometers, and can carry horizontal/vertical, front/rear drive or four-wheel drive structures including powertrain, transmission, and rear axle, or even a whole vehicle.

Since steering wheel torque feedback is one of the crucial factors for drivers to gain road feel and ensure driving safety, it is especially important to simulate the steering torque feedback for a driving simulator. At present, steering wheel feedback torque is mainly simulated by an electric motor with gear transmission. The torque response is typically slow, which can result in drivers’ discomfort and poor driving maneuverability. This paper presents a novel torque feedback device with magnetorheological (MR) fluid and coil spring. A phase separation control method is also proposed to control its feedback torque, including spring and damping torques respectively. The spring torque is generated by coil spring, the angle of coil spring can be adjusted by controlling a brushless DC motor. The damping torque is generated by MR fluid, the damping coefficient of MR fluid can be adjusted by controlling the current of excitation coil.

As one of advanced driver assistance systems (ADAS), automatic parking system has great market prospect and application value. In this paper, based on an intelligent vehicle platform, an automatic parking system is designed by using multi-point preview theory. The vehicle kinematics model was established, based on Ackermann steering principle. By analyzing working conditions of parallel parking, complex constraint condition of parking trajectory is established and reference trajectory based on sine wave is proposed. In addition, combined with multi-point preview theory, the design of trajectory following controller for automatic parking is completed. The cost function is designed, which consider the trajectory following effect and the degree of easy handling. The optimization of trajectory following control is completed by using the cost function.

To meet the new requirements of braking system for modern electrified and intelligent vehicles, various novel electro-mechanical brake boosters (Eboosters) are emerging. This paper is aimed at a new type of the Ebooster, which is mainly consisted of a permanent magnet synchronous motor (PMSM), a two-stage reduction transmission and a servo mechanism. Among them, the PMSM is a vital actuator to realize the functions of the Ebooster. To get fast response of the Ebooster system, a novel control strategy employing a maximum torque per ampere (MTPA) control with current compensation decoupling and current-adjusting adaptive flux-weakening control is proposed, which requires the PMSM can operate in a large speed range and maintain a certain anti-load interference capability. Firstly, the wide speed control strategy for the Ebooster’s PMSM is designed in MATLAB/Simulink.

Pneumatic Electric Braking System (EBS) is getting widely spread for commercial vehicles. Pneumatic EBS improves the problem of slow response of traditional pneumatic braking system by implementing brake-by-wire. However, the time-delay response and hysteresis of some electro-pneumatic components and some other issues decrease the response and control accuracy of the pneumatic EBS.

Due to growing interest in automated driving, the need for better understanding of human driving behavior in uncertain environment, such as driving behavior at un-signalized crossroad and roundabout, has further increased. Driving behavior at roundabout is greatly influenced by different dynamic factors such as speed, distance and circulating flow of the potentially conflicting vehicles, and drivers should choose whether to leave or wait at the upcoming exit according to these factors. In this paper, the influential dynamic factors and driving behavior characteristics at the roundabout is analyzed in detail, random forest method is then deployed to predict the driving behavior. For training the driving behavior model, four typical roundabout layouts were created under a real-time driving simulator with PanoSim-RT and dSPACE. Traffic participants with different motion style were also set in the simulation platform to mimic real driving conditions.

Driving assistance system is regarded as an effective method to improve driving safety and comfort and is widely used in automobiles. However, due to the different driving styles of different drivers, their acceptance and comfort of driving assistance systems are also different, which greatly affects the driving experience. The key to solving the problem is to let the system understand the driving style and achieve humanization or personalization. This paper focuses on clustering and identification of different driving styles. In this paper, based on the driver's real vehicle experiment, a driving data acquisition platform was built, meanwhile driving conditions were set and drivers were recruited to collect driving information. In order to facilitate the identification of driving style, the correlation analysis of driving features is conducted and the principal component analysis method is used to reduce the dimension of driving features.

In this paper, the dynamic stress of the front subframe of a passenger car was obtained using modal stress recovery method to estimate the fatigue life. A finite element model of the subframe was created and its accuracy was checked by modal test in a free hanging state. Furthermore, the whole vehicle rigid-flexible coupling model of the passenger car was built up while taking into account the flexibility of the subframe. Meanwhile, the road test data was used to verify the validity of the dynamic model. On this basis, the modal displacement time histories of the subframe were calculated by a dynamic simulation on virtual proving ground consisting of Belgian blocks, cobblestone road and washboard road. By combining the modal displacement time histories with modal stress tensors getting from normal mode analysis, the dynamic stress time histories of the subframe were obtained through modal stress recovery method.

This paper presents the feasibility study of using the worldwide harmonized light vehicles test cycle (WLTC) for the fuel consumption certification of Chinese Light-duty (LD) vehicles. First, the key steps and the technical routes of the development process of WLTC are summarized. Second, the operation data of 3082 vehicles in 41 typical cities of China are collected throughout the year. Then, the characteristics of the acquisition data are compared with WLTC. Finally, the feasibility of using WLTC for fuel consumption certification of Chinese LD vehicles is analyzed in three aspects, includes operation characteristics, weighting factors and fuel consumption. The result shows that there is obvious difference between WLTC and Chinese reality, and WLTC is not suitable for the fuel consumption certification of Chinese LD vehicles.