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This paper proposes a novel allocation-based control method for four-wheel independently actuated electric vehicles. In the proposed method, both actuator dynamics and input/output constraints are fully taken into consideration in the control design. First, the actuators are modeled as first-order dynamic systems with delay. Then, the control allocation is formulated as an optimization problem, with the primary objective of minimizing errors between the actual and desired control outputs. Other objectives include minimizing the power consumption and the slew rate of the actuator outputs. As a result, this leads to frequency-dependent allocation that reflects the bandwidth of each actuator. To solve the optimization problem, an efficient numerical algorithm is employed. Finally the proposed control allocation method is implemented to control a four-wheel independently actuated electric vehicle.

In this article, the regenerative braking system is designed, which can realize the torque allocation between electric braking and hydraulic braking, where the cost function designed in this article considers factors of braking torque following effect, energy regenerative power, and hydraulic braking consumed power. In addition, a complete anti-lock braking system (ABS) is designed, which is based on regenerative braking. With the optimal slip ratio as control target, target wheel speed, control wheel speed, braking torque control strategy, and enable/disenable control logic of ABS are determined. By MATLAB/Simulink-DYNA4 co-simulation and real vehicle test, the feasibility and applicability of ABS based on regenerative braking are verified, under the condition of small severity of braking.

The evaluation of electric vehicle electric/electronic-architectures (e/e-architectures) is the main topic of this paper. The electric vehicle is chosen as an example system, as it reflects the typical challenges of modern vehicle e/e-architecture development. The development of modern automotive technology also presents another important trend - vehicle electrification. New electric and electronic devices are developed and required in the automotive industry and control commands are exchanged by electric and electronic ones. The energy storage systems (ESS) properly reflect the above two aspects. The energy storage device also takes care of the peak loads, the high load dynamics, and it utilizes the braking energy in order to increase the efficiency. In this work a Li-ion battery and an ultracapacitor both are considered as energy storage devices.

This paper presents a unified novel function-based brake control architecture, which is designed based on a top-down approach with functional abstraction and modularity. The proposed control architecture includes a commands interpreter module, including a driver commands interpreter to interpret driver intention, and a command integration to integrate the driver intention with senor-guided active driving command, state observers for estimation of vehicle sideslip, vehicle speed, tire lateral and longitudinal slips, tire-road friction coefficient, etc., a commands integrated control allocation module which aims to generate braking force and yaw moment commands and provide optimal distribution among four wheels without body instability and wheel lock or slip, a low-level control module includes four wheel pressure control modules, each of which regulates wheel pressure by fast and accurate tracking commanded wheel pressure.

To cope with the conflict requirements between the stability and handling performance, and the high-order and complex vehicle-trailer plant, a model tracking method is proposed. With this approach, a feedback control is designed to “decouple” the vehicle and the trailer plant, such that each tracks a well-defined second-order reference model independently yet coordinately. A feedforward control is designed to maintain its system steady-state performance. As a result, the proposed approach not only improves the system transient responses, but also its steady-state performance. This approach further yields a simple yet analytical control derivation that provides more insight to the system dynamics.

Simulation has been considered as one of the key enablers on the development and testing for autonomous driving systems as in-vehicle and field testing can be very time-consuming, costly and often impossible due to safety concerns. Accurately modeling traffic, therefore, is critically important for autonomous driving simulation on threat assessment, trajectory planning, etc. Traditionally when modeling traffic, the motion of traffic vehicles is often considered to be deterministic and modeled based on its governing physics. However, the sensed or perceived motion of traffic vehicles can be full of errors or inaccuracy due to the inaccurate and/or incomplete sensing information. In addition, it is naturally true that any future trajectories are unknown. This paper proposes a novel modeling method on traffic considering its motion uncertainties, based on Gaussian process (GP).

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.

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.

Although advanced driver assistance systems (ADAS) have been widely introduced in automotive industry to enhance driving safety and comfort, and to reduce drivers’ driving burden, they do not in general reflect different drivers’ driving styles or customized with individual personalities. This can be important to comfort and enjoyable driving experience, and to improved market acceptance. However, it is challenging to understand and further identify drivers’ driving styles due to large number and great variations of driving population. Previous research has mainly adopted physical approaches in modeling drivers’ driving behavior, which however are often very much limited, if not impossible, in capturing human drivers’ driving characteristics. This paper proposes a reinforcement learning based approach, in which the driving styles are formulated through drivers’ learning processes from interaction with surrounding environment.

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.

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.

A vehicle dynamics stability control system based on integrated-electro-hydraulic brake (I-EHB) system with hierarchical control architecture and nonlinear control method is designed to improve the vehicle dynamics stability under extreme conditions in this paper. The I-EHB system is a novel brake-by-wire system, and is suitable to the development demands of intelligent vehicle technology and new energy vehicle technology. Four inlet valves and four outlet valves are added to the layout of a conventional four-channel hydraulic control unit. A permanent-magnet synchronous motor (PMSM) provides a stabilized high-pressure source in the master cylinder, and the four-channel hydraulic control unit ensures that the pressures in each wheel cylinder can be modulated separately at a high precision. Besides, the functions of Anti-lock Braking System, Traction Control System and Regenerative Braking System, Autonomous Emergency Braking can be integrated in this brake-by-wire system.

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.

Steering torque feedback, or steering feel, is widely regarded as an important aspect of driver interface to road feel. To generate a steering feel with the appropriate level of fidelity required by a driver-vehicle system or a driving simulator, it is essential to gain a good understanding of various important influencing factors of steering torque feedback. This paper presents a comprehensive study and analysis of internal and external factors that strongly affect steering torque feedback. A steering torque feedback model with sufficient fidelity is established and verified as the base for this study. The individual- and collective-level influences of these factors on steering torque feedback are analyzed in both time domain and frequency domain, with guidelines provided on how to properly use these influencing factors to control their negative effects in modeling steering torque feedback.

Brake-by-wire (BBW) system has drawn a great attention in recent years as driven by rapidly increasing demands on both active brake controls for intelligent vehicles and regenerative braking controls for electric vehicles. However, unlike conversional brake systems, the reliability of the brake-by-wire systems remains to be challenging due to its lack of physical connection in case of system failure. There are various causes for the failure of a BBW system, such as failure of brake controller, loss of sensor signals, failure of communication or even power supply, to name a few. This paper presents a fault-tolerant control under novel control architecture. The proposed control architecture includes a driver command interpreter module, a command integration module, a control allocation module, a fault diagnosis module and state observers. The fault-tolerant control is designed based on a quadratic optimal control method with consideration of actuator constraints.

The permanent-magnet DC motor, which is directly connected to the hydraulic pump, is a significant component of hydraulic control unit (HCU) in an anti-lock braking system (ABS). It drives the pump to dump the brake fluid from the low-pressure accumulator back to master cylinder and makes sure the pressure decreases of wheel cylinder in ABS control. Obviously, the motor should run fast enough to provide sufficient power and prevent the low-pressure accumulator from fully charging. However, the pump don't need always run at full speed for the consideration of energy conservation and noise reduction. Therefore, it is necessary to accurately regulate the speed of the DC motor in order to improve quality of ABS control. In this paper, an accurate speed control algorithm was developed for the permanent-magnet DC motor of the ABS to implement the performance of the system, reduce the noise and save the energy in the meanwhile.

This paper presented an engineering review on the state of the art in the research and development of vehicle-trailer handling dynamics and stability controls. The issues and potential technical solutions were identified in various areas and the unique characteristics of vehicle-trailer as a combined system were investigated and compared to a single-unit vehicle system. Many approaches taken in modeling, analysis, simulation and testing were examined, and various control methods, actuations and control implementations were evaluated. As a result of this study, further research areas were also identified. While it is important to maintain the stability of a trailer, thus the stability of a vehicle-trailer combination, it remains one of the major challenges in designing an appropriate control law to balance effectively the requirements between stability and handling performance, which often set conflicting objectives.