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The adhesion control is the basic technology of active safety for the four-wheel driven EV. In this paper, a novel adhesion control method based on fuzzy logic control is proposed. The control system can maximize the adhesion force without road condition information and vehicle speed signal. Also, the regulation torque to prevent wheel slip is smooth and the vehicle driving comfort is greatly improved. For implementation, only the rotating speed of the driving wheel and the motor driving torque signals are needed, while the derived information of the wheel acceleration and the skid status are used. The simulation and road test results have shown that the adhesion control method is effective for preventing slip and lock on the slippery road condition.

During a car launch, the driving torque from driveline acts on brake disk, and may lead the pad to slip against the disk. Especially with slow brake pedal release, there is still brake torque applies on the disk, which will retard the rotation of disk, and under certain conditions, the disk and pad may stick again, so the reciprocated stick and slip can induce the noise and vibration, which can be transmitted to a passenger by both tactile and aural paths, this phenomenon is defined as brake groan. In this paper, we propose a nonlinear dynamics model of brake for bidirectional, and with 7 Degrees of Freedom (DOFs), and phase locus and Lyapunov Second Method are utilized to study the mechanism of groan. Time-frequency analysis method then is adopted to analyze the simulation results, meanwhile a test car is operated under corresponding conditions, and the test signals are sampled and then processed to acquire the features.

In this study, the vibroacoustic characteristics and torque fluctuation of switched reluctance motors (SRMs) with different phases and poles have been analyzed in detail. Also, the common four SRMs, i.e., three-phase 6/4 SRM, four-phase 8/6 SRM, five-phase 10/8 SRM, and six-phase 12/10 SRM, have been selected. First, the spatial-temporal distribution characteristics of radial force in SRMs were revealed by virtue of the analytical derivation, which was validated by the 2D Fourier decomposition based on the finite-element results of radial force. Second, a multiphysics model, which was composed of an electromagnetic field, a mechanical field, and an acoustic field, was established to predict the noise behaviors of SRMs with different phases and poles. Third, the relationship between the torque fluctuation and the phases / poles of SRMs, and the relationship between the noise and the radial force / phases / poles are all analyzed.

Recently, electro-hydraulic brake systems (EHB) has been developed to take place of the vacuum booster, having the advantage of faster pressure build-up and continuous pressure regulation. In contrast to the vacuum booster, the pressure estimation for EHB is worth to be studied due to its abundant resource (i.e. electric motor) and cost-effective benefit. This work improves an interconnected pressure estimation algorithm (IPEA) based on actuator characteristics by introducing the vehicle dynamics and validates it via vehicle tests. Considering the previous IPEA as the prior pressure estimation, the wheel speed feedback is used for modification via a proportional-integral (PI) observer. Superior to the IPEA based on actuator characteristics, the proposed PEA improves the accuracy by more than 20% under the mismatch of pressure-position relation.

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.

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.

Driving posture study is essential for the evaluation of the occupant packaging. This paper presents a method of reconstructing driver’s postures in a real vehicle using a 3D laser scanner and Human Builder (HB), the digital human modeling tool under CATIA. The scanning data was at first converted into the format readable by CATIA, and then a personalized HB manikin was generated mainly using stature, sitting height and weight. Its pelvis position and joint angles were manually adjusted so as to match the manikin with the scan envelop. If needed, a fine adjustment of some anthropometric dimensions was also preceded. Finally the personalized manikin was put in the vehicle coordinate system, and joint angels and joint positions were extracted for further analysis.

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 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.

Vehicle sideslip angle is significant for electronic stability control devices and hard to estimate due to the nonlinear and uncertain vehicle and tire dynamics. In this paper, based on the two track vehicle dynamic model considering the tire pneumatic trail variation, the vehicle sideslip angle estimation method was proposed. First, the extra steering angle of each wheel caused by kinematics and compliance characteristics of the steering system and suspension system was analyzed. The steering angle estimation method was designed. Since the pneumatic trail would vary with different tire slip angle, distances between the center of gravity (COG) and front&rear axle also change with the tire slip angle. Then, based on the dynamic pneumatic trail and estimated steering angle, we modified the traditional two track vehicle dynamic model using a brush tire model. This model matches the vehicle dynamics more accurately.

Vehicle sideslip angle estimation is of great importance to the vehicle stability control as it could not be measured directly by ordinary vehicle-mounted sensors. As a result, researchers worldwide have carried out comprehensive research in estimating the vehicle sideslip angle. First, as the attitude would affect the acceleration information measured by the IMU directly, different kinds of vehicle attitude estimation methods with multi-sensor fusion are presented. Then, the estimation algorithms of the vehicle sideslip angle are classified into the following three aspects: kinematic model based method, dynamic model based method, and fusion method. The characteristics of different estimation algorithms are also discussed. Finally, the conclusion and development trend of the sideslip angle estimation are prospected.

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.

Based on the four-wheel-drive electric vehicle (4WD EV), a variable structure control (VSC) strategy is designed in this paper for the anti-lock braking control. With nonpeak friction coefficient as target, sign judgment method of switch function in this VSC strategy is improved and a new control algorithm is proposed. The improved VSC strategy is made robust to the parameters of the algorithm and verified by the computer simulation as well as the hard-in-loop test. The results show that the slip rate can be controlled to a point in the stable area near the optimal slip ratio and the control strategy can effectively realize the anti-lock braking control.

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.

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.