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As a novel assist actuator of brake system, the electromechanical brake (EMB) booster has played a significant role in the battery electric vehicles and automatic driving vehicles. It has advantages of independent to vacuum source, active braking, and tuning pedal feeling compared with conventional vacuum brake booster. In this article, a novel EMB booster system is proposed, which is consisted of a permanent magnet synchronous motor (PMSM), a two-stage reduction by gears and ball screw, a servo body, and a reaction disk. Together with the hydraulic control unit, it has two working modes: active braking for automatic drive and passive braking for driver intervention. The structure and work principle of the electric brake booster system is first introduced. The precise control from pedal force to hydraulic pressure is the key for such a power-assisted brake actuator. We translate the control problem of force feedback control to position tracking control.

With more and more countries proposing timetables for stopping selling of fuel vehicles, China has also issued a “dual-slope” policy. As electric vehicles are the most promising new energy vehicle, which is worth researching. The integration and control of the motor and gearbox have gradually become a hot research topic due to low cost with better performance. This paper takes an electric vehicle equipped with permanent magnet synchronous motor and two-gear automatic transmission without synchronizer and clutch as the research object.

The motor errors of the four-wheel independent driving electric vehicles was studied, and classified as steady errors and dynamic errors. In the paper, the forward compensation control and the PID control strategy were respectively applied to compensate for the errors. The electric vehicles straight-line running stability caused by the motor errors was discussed, the PID control method based on BP neural net work was presented to co-ordinate torque of the wheels. The result of the simulation on the 7 degrees of freedom vehicle model showed that control method improved the straight-line running ability of the vehicle.

A new lateral stability control method, which is based on vehicle sideslip angle and tire cornering stiffness estimation, is proposed to improve the lateral stability of the four-in-wheel-motor-driven electric vehicle (FIWMD-EV) in this paper. Through the lateral tire force information, vehicle sideslip angle can be estimated by the extended kalman filter (EKF). Using the estimated vehicle sideslip angle, tire cornering stiffness can be also estimated by forgetting factor recursive least squares (FFRLS). Furthermore, combining with the vehicle dynamics model, an adaptive control target model is proposed with the information on vehicle sideslip angle and tire cornering stiffness. The new lateral stability control system uses the direct yaw moment control (DYC) based on dynamic sliding mode is proposed. The performance and effectiveness of the proposed vehicle state estimation and lateral stability control system are verified by CarSim and Simulink cosimulation.

The primary noise sources of electric vehicles differ from that of traditional vehicles due to the fundamental differences in their powertrain architecture. In this work, some exterior noise test methods for electric vehicles are briefly introduced first, which include a pass-by noise measurement method during acceleration on the proving ground as well as a similar measurement in a semi-anechoic room. The obtained results based on those two methods from a production electric vehicle are compared and analyzed. Then the mechanism of the source, path, and contribution is illustrated, and a model of path-source-contribution for electric vehicles is established. The model validation is subsequently carried out by correlating the calculated outcomes with the measured results under real operating conditions. Finally, by using the model, contribution analyses are carried out to identify the primary exterior noise sources.

Since road electric vehicles typically require a significantly variable and random load power demand in response to traffic conditions, such as frequent sequences of acceleration and deceleration and uphill followed by downhill runs. In this context, the energy management system of electric vehicle must ensure an effective power distribution between battery and supercapacitor to satisfy load demand. In this paper, the power management control strategy of hybrid energy storage system is developed by introducing terrain information to optimize system efficiency and battery lifetime. In this presented research, we aim at developing a power management control strategy considering the influence of the terrain information on system efficiency and battery lifetime.

Direct yaw moment control can maintain the vehicle stability in critical situation. For four-wheel independently driven (4WD) electric vehicle with in-wheel motors (IWMs), direct yaw moment control (DYC) can be easily achieved. A fairly accurate calculation of the required yaw moment can improve vehicle stability. A novel sliding mode control (SMC) technique is employed for the motion control so as to track the desired vehicle motion, which is it for different working circumstances compared to the well-used traditional DYC. Through the weighted least square algorithm, the lower controller is used to determine the torque properly allocated to each wheel according to the desired yaw moment. Several actuator constraints are considered in the control strategy. In addition, a nonlinear tire model is utilized to improve the accuracy of tire lateral force estimation. Then, simulations are carried out and the values of vehicle states are compared.

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.

With rapid development of the automobile industry and the growing maturity of the automotive electronic technologies, the distributed-traction electric vehicle with four-wheel-distributed steering/braking/traction systems is regarded as an important development direction. With its unique chassis structure, it is the ideal benchmark platform used to evaluate active safety systems. The distributed-traction electric vehicle with four-wheel-distributed steering system is essentially full drive-by-wire vehicle. With its flexible chassis layout and high control degrees-of-freedom, the full drive-by-wire electric vehicle acted as a kind of redundant system is an ideal platform for the research of integrated control. In this treatise, the longitudinal dynamics of the electric vehicle as well as its lateral and yaw motions are controlled simultaneously.

Omni-directional electric vehicle built by our research group is an advanced electric vehicle whose four wheels can drive, steer and brake independently. The vehicle chassis system is composed of four in-wheel motors, four independent steer motors and electromagnetic brake system, and its control system is divided into logical control layer and underlying execution layer. The information exchange between these two layers is implemented by CAN bus. In this paper, the traction control logic for Omni-directional electric vehicle is developed. The study mainly involves two aspects: the vehicle states estimation and the traction control logic design. The vehicle states, including vehicle longitudinal velocity, lateral speed, side slip angle and yaw rate, etc, are estimated based on Extended Kalman Estimation and multiple degrees of freedom vehicle model.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

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.

The intelligent and electric vehicles are the future of vehicle technique. The development of intelligent and electric vehicles also promotes new requirements to many traditional chassis subsystems, including traditional braking system equipped with vacuum boosters. The Electro-Mechanical Booster is an applicable substitute of traditional vacuum booster for future intelligent and electric vehicles. It is independent of engine vacuum source, and can be combined with electric regenerative braking. A complete system model is necessary for system analysis and algorithm developing. For this purpose, the modeling of electro-hydraulic braking system is necessary. In this paper, a detailed electro-hydraulic braking system model is studied. The system consists of an electro-mechanical booster and hydraulic braking system. The electro-mechanical booster which mainly contains a permanent magnet synchronous motor (PMSM) and a set of transmission mechanism is the critical component.

Minimum energy consumption with maximum comfort driving experience define the ideal human mobility. Recent technological advances in most Advanced Driver Assistance Systems (ADAS) on electric vehicles not only present a significant opportunity for automated eco-driving but also enhance the safety and comfort level. Understanding driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system comfort. This research focuses on the personalized and green adaptive cruise control for intelligent electric vehicle, which is also known to be MyEco-ACC. MyEco-ACC is based on the optimization of regenerative braking and typical driving styles. Firstly, a driving style model is abstracted as a Hammerstein model and its key parameters vary with different driving styles. Secondly, the regenerative braking system characteristics for the electric vehicle equipped with 4-wheel hub motors are analyzed and braking force distribution strategy is designed.

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.

A full drive-by-wire electric vehicle, named Urban Future Electric Vehicle (UFEV) is developed, where the four wheels' traction and braking torques, four wheels' steering angles, and four active suspensions (in the future) are controlled independently. It is an ideal platform to realize the optimal vehicle dynamics, the marginal-stability and the energy-efficient control, it is also a platform for studying the advanced chassis control methods and their applications. A centralized control system of hierarchical structure for UFEV is proposed, which consist of Sensor Layer, Identification and Estimation Layer, Objective Control Layer, Forces and Motion Distribution Layer, Executive Layer. In the Identification and Estimation Layer, identification model is established by utilizing neural network algorithms to identify the driver characteristics. Vehicle state estimation and road identification of UFEV based on EKF and Fuzzy Logic Control methods is also conducted in this layer.

Hybrid Electric Vehicles with a power split system provide a variety of possibilities to promote the fuel economy of vehicles and better adapt to various driving conditions. In this paper, a new power split system of a hybrid electric bus which consists of double planetary gear sets and a clutch is introduced. The system is able to decouple both the torque and speed of the engine from the road load, which makes it possible for the engine to operate on its optimal operation line (OOL). Considering the features of the system configuration and bus driving cycle, the driving mode of the bus is divided into Electric Vehicle (EV) mode, Electric Variable Transmission (EVT) mode and Parallel mode. By controlling the engagement of the clutch at high vehicle speed (after the mechanical point), the system operates in the parallel mode rather than EVT mode. This avoids the problem that the system efficiency sharply declines in high speed region which EVT configurations are generally faced with.

In order to improve the vehicle economy of electric vehicles, this paper first analyzes the energy-saving mechanism of electric vehicles. Taking the energy consumption of the deceleration process as a starting point, this paper deeply analyzes the energy consumption of the deceleration process under several different control modes by the test data, so as to obtain two principles that should be followed in energy-saving control strategy. Then, an intelligent deceleration energy-saving control strategy by getting the forward vehicle information is developed. The overall architecture of the control strategy consists of three parts: information processing, target calculation and torque control. The first part is mainly to obtain the forward vehicle information from the perception systems, and the user's habits information from big data, and this information is processed for the next part.

Noise excitation sources are different between electric vehicles and conventional vehicles due to their distinct propulsion system architecture. This work focuses on an interior noise contribution analysis by experimental measurements and synthesis approach using a methodology established based on the principle of noise path analysis. The obtained results show that the structure-borne noise from the tire-road excitation acts as a major contributor to the overall interior noise level, and the structure-borne noise from the power plant system contributes noticeably as well, whereas contributions from the electric motor and tire are relatively insignificant.

With the prevalent trend of the pure electric vehicle, vehicle interior noise has been reduced significantly. However, other noises become prominent in the cabin. Especially, the BSR noise generated by friction between parts and the clearance between components become the elements of complaints directly affect the quality of vehicles. Currently, the BSR noises are subjectively evaluated by experts, and the noise samples are simply labeled as ‘qualified’ or ‘unqualified’. Therefore, it is necessary to develop an evaluation model to assess the BSR noise objectively. In this paper, we study the vehicle rattle noise intensively. Several types of rattle noise were recorded in a semi-anechoic room. The recorded signals were then processed in the LMS test lab. to extract the single impact segments. A pool of simulated signals with different impact rates (number of impacts per second) and various loudness was synthesized for analyzation.