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With the increasing worldwide concern on environmental pollution, battery electrical vehicles (BEV) have attracted a lot attention. However, it still couldn’t satisfy the market requirements because of the low battery power density, high cost and long charging time. The range-extended electrical vehicle (REEV) got more attention because it could avoid the mileage anxiety of the BEVs with lower cost and potentially higher efficiency. When internal combustion engine (ICE) works as the power source of range extender (RE) for REEV, its NVH, emissions in starting process need to be optimized. In this paper, a 2-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially connected. Meanwhile, batteries and load systems were equipped. The RE co-control system was developed based on Compact RIO (Compact Reconfigurable IO), Labview and motor control unit (MCU).

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.

This paper describes a methodology to estimate yaw rate of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimate the vehicle yaw rate precisely, especially when some of the four wheels have large slip ratio. Therefore, a model based estimation methodology is put forward, which uses four wheel speeds, steering wheel angle and vehicle lateral acceleration as input signals. Firstly the yaw rate is estimated through three different ways considering both vehicle kinematics and vehicle dynamics. Vehicle kinematics based method has good estimation accuracy even when the vehicle has large lateral acceleration. However, it can not provide satisfying results when the wheel has large slip ratio. In contrast, vehicle dynamics based method is not so sensitive to wheel slip ratio.

Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.

Path following controller of a six-wheel skid-steering vehicle is designed. The vehicle speed is controlled through engine speed control and the lateral vehicle steering is controlled through hydraulic braking on each side. Contrary to the common approaches considering non-holonomic constraints, vehicle dynamic characteristics and nonlinear characteristics of tire are considered. A hierarchical control structure is applied in this vehicle control system. The kinematic controller works out the reference yaw rate and reference vehicle speed. And a robust dynamic controller tracks the reference signal. In addition, the dynamic controller takes actuator ability into account.

With the development of vehicle electrification, electronic hydraulic brake system is gradually applied. Many companies have introduced products related to integrated electronic hydraulic brake system (I-EHB). In this paper, an I-EHB system is introduced, which uses the motor to drive the reduction mechanism as a power source for braking. The reduction mechanism is composed of a turbine, a worm, a gear and a rack. A control method based on command feed-forward is proposed to improve the hydraulic pressure control of I-EHB. Based on previous research, we simplify the system to first order system, and the theoretical design of the command feed-forward compensator is carried out. The feed-forward controller is applied, including the velocity feed-forward and the acceleration feed-forward, to improve the response speed and tracking effect of the system.

In this paper, a novel method is proposed to establish the vehicle yaw stability criterion based on the sideslip angle-yaw rate (β-r) phase plane method. First, nonlinear two degrees of freedom vehicle analysis model is established by adopting the Magic Formula of nonlinear tire model. Then, according to the model in the Matlab/Simulink environment, the β-r phase plane is gained. Emphatically, the effects of different driving conditions (front wheels steering angle, road adhesion coefficient and speed) on the stability boundaries of the phase plane are analyzed. Through a large number of simulation analysis, results show that there are two types of phase plane: curve stability region and diamond stability region, and the judgment method of the vehicle stability domain type under different driving conditions is solved.

Path tracking is the rudimentary capability and primary task for autonomous ground vehicles (AGVs). In this paper, a novel four-wheel-independent-steering (4WIS) and four-wheel-independent-drive (4WID) electric vehicle (EV) is proposed which is equipped with steer-by-wire (SBW) system. For path-tracking controller design, the nonlinear vehicle model with 2 degrees of freedom (DOF) is built utilizing the nonlinear Dugoff tire model. The nonlinear dynamic model of SBW system is conducted as well considering the external disturbances. As to the path-tracking controller design, an integrated four-wheel steering (4WS) and direct yaw-moment control (DYC) system is designed based on the model predictive control (MPC) algorithm to track the target path described by desired yaw angle and lateral displacement. Then, the fast terminal sliding mode controller (FTSMC) is proposed for the SBW system to suppress disturbances.

In this paper, an integrated electronic hydraulic brake(I-EHB) system is introduced, which is mainly composed of a motor, a worm gear, a worm, a gear, a rack etc. The friction leads the system to the creeping phenomenon and the dead zone. These phenomenon seriously affect the response speed and the hydraulic pressure control .In order to realize the accurate hydraulic pressure control of I-EHB system, a new friction compensation control method is proposed based on LuGre dynamic friction model. And the theoretical design of adaptive control method is designed based on the feedback of the master cylinder pressure and the operating state of the system. Then the stability of the control method is proved by Lyapunov theorem. A co-simulation model is built with Matlab/Simulink and AMESim, so as to prove the validity of the control method.

In order to improve the robustness and stability of autonomous vehicle at high speed, a path tracking approach which combines front steering and differential braking is investigated in this paper. A bicycle model with 3-DOFs is established and a linear time-varying predictive model using front steering as its control input can be derived. Based on model predictive theory, the path tracking issue using linear time-varying model predictive control can be transformed into an online quadratic programming problem with constraints. The expected front steering angle can be obtained from online moving optimization. Then the direct yawing control is adopted to treat two types of differential braking control. The first one investigates steady-state gain of yaw rate in linear 2-DOFs vehicle model, and designs a stable differential braking controller which is based on reference yaw rate.

With the introduction of BroadR-Reach and time-sensitive networking (TSN), Ethernet has become an option for in-vehicle networks (IVNs). Although it has been used in the IT field for decades, it is a new technology for automotive, and thus requires extensive testing. Current test solutions usually target specifications rather than the in-vehicle environment, which means that some properties are still uncertain for in-vehicle usage (e.g., fault tolerance for shorted or open wires). However, these characteristics must be cleared before applying Ethernet in IVNs, because of stringent vehicular safety requirements. Because CAN is usually used for these environments, automotive Ethernet is expected to have the same or better level of fault tolerance. Both CAN and BroadR-Reach use a single pair of twisted wires for physical media; thus, the traditional fault-tolerance test method can be applied for automotive Ethernet.

The integrated control system which combines the differential drive assisted steering (DDAS) and the direct yaw moment control (DYC) for the distributed drive electric vehicle (DDEV) is studied. A handling improvement algorithm for the normal cornering maneuvers is proposed based on motion tracking control. Considering the ideal assistant power character curves at different velocities, an open-loop DDAS control strategy is developed to respond the driver’s demand of steering wheel torque. The DYC strategy contains the steering angle feedforward and the yaw rate feedback. The steering angle feedforward control strategy is employed to improve yaw rate steady gain of vehicle. The maximum feedforward coefficients at different velocities are obtained from the constraint of the motor external characteristic, final feedforward coefficients are calculated according to the ideal assistant power character curve of the DDAS.

The coordinated control of stability and steering systems in collision avoidance steering evasion has been widely studied in vehicle active safety area, but the studies are mainly aimed at autonomous vehicle without driver or conventional combustion engine vehicle. This paper focuses on the control of hybrid vehicle integrated with rear hub in emergency steering evasion situation, and considering the driver’s characteristics. First, the mathematics model of vehicle dynamics and driver has been given. Second, based on the planned steering evasion path, the model predictive control method is presented for achieving higher evasion path tracking accuracy under driver’s steering input. The prediction model includes an adaptive preview distance driver model and a vehicle dynamics model to predict the driver input and the vehicle trajectory.

The unscented Kalman filter (UKF) is applied to estimate the real vehicle velocity. The velocity estimation algorithm uses lateral acceleration, longitudinal acceleration and yaw rate as inputs. The non-linear vehicle model and Dugoff tire model are built as the estimation model of UKF. Some parameters of Dugoff tire model and vehicle, which can't be measured directly, are identified by the particle swarm optimization (PSO). For the purpose of evaluating the algorithm, the estimation values of UKF are compared with measurements of the Inertial and GPS Navigation system. Besides, the real time property of UKF is tested by xPC Target, which is a real-time software environment from MathWorks. The result of the real vehicle experiment demonstrates the availability of the UKF and PSO in vehicle velocity estimation.

In this paper we present a path following control design for a six-wheel skid-steering vehicle. Contrary to the common approaches that impose non-holonomic constraints, a dynamic vehicle model is established based on a pseudo-static tire model, which uses tire slip to determine tire forces. Our control system admits a modular structure, where a motion controller computes the reference vehicle yaw rate and reference vehicle speed and a dynamics controller tracks these signals. A robust nonlinear control law is designed to track the reference wheel speeds determined by the dynamics controller with proved stability properties. Saturated control techniques are employed in designing the reference yaw rate, which ensures the magnitude of the reference yaw rate does not violate the constraint from the ground-tire adhesion. The simulation results demonstrate the effectiveness of the proposed path following control design.

This article conducts a research on the active control differential (ACD) yaw moment stability control for central motor driven automobiles. By calculation, the active control differential yaw moment generation ability which is limited by the maximum differential twist ratio and the motor output torque is not enough compared with traditional Electronic Stability Program (ESP). A Matlab and CarSim joint simulation is applied on double lane change and sine wave steering input condition, through which the active control differential effect is analyzed. It is concluded that yaw moment control using active control differential has improved the steering sensitivity and yaw rate tracking effect to some extent in double lane change test and it also has been verified that it works effectively to keep the stability of the vehicle in sine wave test.

Steering of skid-steered vehicles without steering mechanism is realized by differential drive/brake torque generated from in-wheel motors at left and right sides. Compared to traditional Ackerman-steered vehicles, skid-steered vehicles consume much more energy while steering due to greater steering resistance. Torque allocation is critical to the distributed drive skid-steered vehicles, since it influences not only steering performance, but also energy efficiency. In this paper, the dynamic characteristics of six-wheeled skid-steered vehicles were analyzed, and a 2-DOF vehicle model was established, which is important for both motion tracking control and torque allocation. Furthermore, a hierarchical controller was proposed. Considering tire force characteristics and tire slip, the upper layer calculates the generalized force and desired yaw moment based on anti-windup PI (proportion-integral) control method.

To overcome the shortcoming that vehicles with multiple steering modes need to switch steering modes at parking or very low speeds, a dynamic switch method of steering modes based on MOEA/D (Multi-objective Evolutionary Algorithm Based on Decomposition) was proposed for 4WID-4WIS (Four Wheel Independent Drive-Four Wheel Independent Steering) electric vehicle, considering the smoothness of dynamic switch, the lateral stability of the vehicle and the energy economy of tires. First of all, the vehicle model of 4WID-4WIS was established, and steering modes were introduced and analyzed. Secondly, the conditions for the dynamic switch of steering modes were designed with the goal of stability and safety. According to different constraints, the control strategy was formulated to obtain the target angle of the active wheels. Then aiming at the smoothness of the dynamic switch, the active wheel angle trajectory was constructed based on the B-spline theory.

Due to the differences in traffic situations and traffic safety laws, standards for extraction of critical driving scenarios (CDSs) vary from different countries and areas around the world. To maintain the characteristic variables under the Chinese typical CDSs, this paper uses the three-layer detection method to extract and detect CDSs in the Natural Driving Data from China-FOT project which executing under the real traffic situation in China. The first layer of detection is mainly based on the feature distributions which deviate from normal driving situations. These distributions associated with speed and longitudinal acceleration/lateral acceleration/yaw rate also quantify the critical levels classification.

Lane Keeping Assistance (LKA) system is a very important part in Advanced Driver Assistance Systems (ADAS). It prevents a vehicle from departing out of the lane by exerting intervention. But an inappropriate performance during LKA intervention makes driver feel uncomfortable. The intervention of LKA can be divided into 3 parts: intervention timing, intervention process and intervention ending. Many researches have studied about the intervention timing and ending, but factors during intervention process also affect driver feelings a lot, such as yaw rate and steering wheel velocity. To increase driver’s acceptance of LKA, objective and subjective tests were designed and conducted to explore important indices which are highly correlated with the driver feelings. Different kinds of LKA controller control intervention process in different ways. Therefore, it’s very important to describe the intervention process uniformly and objectively.