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Vehicle Longitudinal Control (VLC) algorithm is the basis function of automotive Cruise Control system. The main task of VLC is to achieve a longitudinal acceleration tracking controller, performance requirements of which include fast response and high tracking accuracy. At present, many control methods are used to implement vehicle longitudinal control. However, the existing methods are need to be improved because these methods need a high accurate vehicle dynamic model or a number of experiments to calibrate the parameters of controller, which are time consuming and costly. To overcome the difficulties of controller parameters calibration and accurate vehicle dynamic modeling, a vehicle longitudinal control algorithm based on iterative learning control (ILC) is proposed in this paper. The algorithm works based on the information of input and output of the system, so the method does not require a vehicle dynamics model.

The tire mechanics characteristics are essential for analysis, simulation and control of vehicle dynamics. This paper develops the UniTire model for tire forces and moments under combined slip conditions with anisotropic tire slip stiffness. The anisotropy of tire slip stiffness, which means the difference of tire longitudinal slip stiffness and cornering stiffness, will cause that the direction of tire resultant shear stress in adhesion region is different from that in sliding region. Eventually the tire forces and moments under combined slip conditions will be influenced obviously. The author has proposed a “direction factor” before to modify the direction of resultant force in the tire-road contact patch, which can describe tire forces at cornering/braking combination accurately. However, the aligning moments which are very complicated under combined slip conditions are not considered in previous analysis.

The tire mechanics characteristics are essential for analysis and control of vehicle dynamics. Basically, the effects of sideslip, longitudinal slip, camber angle and vertical load are able to be represented accurately by current existing tire models. However, the research of velocity effects for tire forces and moments are still insufficient. Some experiments have demonstrated that the tire properties actually vary with the traveling velocity especially when the force and moment are nearly saturated. This paper develops an enhanced brush tire model and the UniTire semi-physical model for tire forces and moments under different traveling velocities for raising need of advanced tire model. The primary effects of velocity on tire performances are the rubber friction distribution characteristics at the tire-road interface.

This paper proposes a dynamic obstacle avoidance system to help autonomous vehicles drive on high-speed structured roads. The system is mainly composed of trajectory planning and tracking controllers. The potential field (PF) model is introduced to establish a three-dimensional potential field for structured roads and obstacle vehicles. The trajectory planning problem that considers the vehicle’s and tires’ dynamics constraints is transformed into an optimization problem with muti-constraints by combining the model predictive control (MPC) algorithms. The trajectory tracking controller used in this paper is based on the 7 degrees of freedom (DOF) vehicle model and the UniTire tire model, which was discussed in detail in previous work [25, 26]. The controller maintains good trajectory tracking performance even under extreme driving conditions, such as roads with poor adhesion conditions, where the car’s tires enter the nonlinear region easily.

To improve the quantitative accuracy of vehicle vibration studies, a roller contact tire model with the geometric filtering concept and a method to determine the effective road input are proposed. Computer simulation with the 13 DOF vehicle model for a light truck, based on two different tire models, and relevant outdoor tests for measuring the vehicle accelerations of both sprung and unsprung masses are presented. Comparisons of test data and simulation results show that the roller contact tire model renders much better simulation accuracy than the single point contact tire model. It is concluded that the roller contact tire model is a powerful concept which acts as a geometric filter, giving a simple method to calculate the enveloping effects of tires and the effective road elevation input.

The properties of contact patch are key factors for tire modeling. Researchers have paid more attention to the contact patch shape and vertical pressure distribution. Some innovative concepts, such as Local Carcass Camber, have been presented to explain special tire modeling phenomena. For a pragmatic tire model, a concise model structure and fewer parameters are considered as the primary tasks for the modeling. Many empirical tire models, such as the well-known Magic Formula model, would become more complex to achieve satisfactory modeling accuracy, due to increasing number of input variables, so the semi-empirical or semi-physical modeling method becomes more attractive. In this paper, the concept of Tire Carcass Camber is introduced first. Different from Local Carcass Camber, Tire Carcass Camber is an imaginary camber angle caused only by lateral force on the unloaded tire.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

Four-wheel-drive electric vehicles (4WD Evs) utilize in-wheel electric motors and Electro-Hydraulic Braking system (EHB). Then, all wheels torque can be controlled independently, and the braking pressure can be controlled more accurately and more fast than conventional braking system. Because of these advantages, 4WD Evs have potential applications in control engineering. In this paper, the in-wheel electric motors and EHB are applied as actuators in the vehicle stability control system. Based on the Direct Yaw-moment Control (DYC), the optimized wheel force distribution is given, and the coordination control of the hydraulic braking and the motor braking torque is considered. Then the EHB hardware-in-the-loop test bench is established in order to verify the effectiveness of the vehicle stability control algorithm through experiments.

Simulations of tire cornering properties with small-amplitude lateral inputs are carried out in non-steady state conditions. The simulation algorithm is derived and the discrete expressions are presented in detail. Based on the simulations, lateral force and aligning moment can be calculated numerically with time-varying yaw angle and lateral displacement as inputs in spatial domain. The flexibility of both tread and carcass along with tire width is taken into account effectively in the simulations, in which the flexibility of carcass includes translating, bending and twisting flexibility. The simulations in non-dimensional form are associated with four tire structure parameters only, which are non-dimensional parameters reflecting the characteristics of tire stiffness, tire width and contact length. Simulation results are validated by test data from step lateral inputs tests. Several typical simulation results are provided.

Under complex and extreme operating conditions, the road adhesion coefficient emerges as a critical state parameter for tire force analysis and vehicle dynamics control. In contrast to model-based estimation methods, intelligent tire technology enables the real-time feedback of tire-road interaction information to the vehicle control system. This paper proposes an approach that integrates intelligent tire systems with machine learning to acquire precise road adhesion coefficients for vehicles. Firstly, taking into account the driving conditions, sensor selection is conducted to develop an intelligent tire hardware acquisition system based on MEMS (Micro-Electro-Mechanical Systems) three-axis acceleration sensors, utilizing a simplified hardware structure and wireless transmission mode. Secondly, through the collection of real vehicle experiment data on different road surfaces, a dataset is gathered for machine learning training.

With the worldwide trends in mobile electrification, consumers' demand for fast charging of electric vehicles (EVs) continues to grow. However, due to the defects of the current mainstream vehicle-mounted lithium-ion batteries (LIBs), lithium plating will occur at the anode during charging at high current rates, reducing battery life and even causing serious safety problems. In this paper, a pseudo two-dimensional (P2D) model integrated with lithium plating and SEI growth reaction is established to simulate the aging behavior of the battery during the cycle aging process. After verifying the model, we set up simulation conditions to quantitatively analyze the relationship between battery operating temperature, charging rate and cycle life, as well as the causes of capacity attenuation under each operating condition.

According to the process that a new driver becomes a low skill level driver and finally a skilled driver from learning how to drive, especially in light of the understanding on the vehicle lateral dynamics that will change from linear characteristic under low speed to strong nonlinear character under high speed, a novel driver model is established. At low speed linear range, off-line optimization based on genetic tuning is introduced into the model to get the optimal control parameters which is viewed as a basic understanding of the vehicle dynamic characteristics of a low skill level driver. On basis of the previous established model, neural network adaptive mechanism is introduced to the driver model which enables the driver to adjust the control online even at high speed non-linear area, reflecting a deeper understanding of the vehicle dynamic model. At last, simulation has been taken in order to verify the correctness and accuracy of the model.

A closed-loop comprehensive evaluation and a test method for vehicle handling and stability have been studied by using development driving simulator. Simulator test scheme has been designed and carried out with 14 vehicle configurations, and subjective evaluation has been made for easy handling of vehicle by drivers. A closed-loop comprehensive evaluation index has been put forward considering the factors affecting vehicle handling and stability. The reliability of the index has been validated by driver's subjective evaluation. A driver/vehicle/ road closed-loop system model has been established, and the theoretical predictive evaluation has been carried out with 14 vehicle configurations. Simulation showed that similar result for both theoretical predictive evaluation and subjective evaluation.

This paper describes a novel recognition and classification method of vehicle targets in urban road based on a vehicle-mounted Velodyne HDL64E light detection and ranging (LIDAR) system. The autonomous vehicle will choose different driving strategy according to the surrounding traffic environments to guarantee that the driving is safe, stable and efficient. It is helpful for controller to provide the efficient stagey to know the exact type of vehicle around. So this method concentrates on reorganization and classification the type of vehicle targets so that the controller can provide a safe and efficient driving strategy for autonomous ground vehicles. The approach is targeted at high-speed ground vehicle, so real-time performance of the method plays a critical role. In order to improve the real-time performance, some methods of data preprocessing should be taken to simplify the large-size long-range 3D point clouds.

This paper presents a torque distribution algorithm to improve the energy efficiency of four-wheel-drive (4WD) electric vehicles with PMSM hub motors. In order to optimize the torque distribution method, at first the motor model considering the affect of iron loss and the loss model of multi-motors drive system of 4WD electric vehicle with PMSM hub motors, which operate at straight-line condition, are established. Besides, realize the online identification of motor parameters based on the MARS, which is important for updating the loss model parameters of the motor drive system. By doing this, the ideal torque distribution ratio can be obtained from the loss model in real-time. The simulation result using different distribution algorithms shows that the optimized torque distribution algorithm based on the loss model can be useful for improving the energy efficiency.

A novel predictable tire model has been proposed for combined braking and cornering forces, which is based on only a few pure baking and pure cornering tests. It avoids elaborate testing of all kinds of combinations of braking and side forces, which are always expensive and time consuming. It is especially important for truck or other large size tires due to the capability constraints of tire testing facilities for combined shear forces tests. In this paper, the predictive model is based on the concept of slip circle and state stiffness method. The slip circle concept has been used in the COMBINATOR model to obtain the magnitude of the resultant force under combined slip conditions; however the direction assumption used in the COMBINATOR is not suitable for anisotropic tire slip stiffness.

In the paper, the Flat Plank Tire Tester of Changchun Automobile Institute is introduced. This paper, according to practical experiences, generalizes some issues in the tire's non-steady state test. In the non-steady state test, it must be assured that the footprint centerline of tire coincides with that of slid platform, which guarantees no sliding motion between tire and slid platform during the movement. Due to tire taper effect and inhomogeneous tire material, when its side slip angle is zero, side force and aligning torque are not zeros, but have initial values. Here two approaches are discussed to eliminate the side force and aligning torque. Besides, other factors in the test are put forward for discussion. Eliminating the interference can obviously improve the test accuracy. This paper also provides test curves of both pure side slip angle input and pure yaw angle input.

One of the most essential factors causing automobile and aircraft shimmy is energy import from road to tires due to tire hysteresis characteristic. The magnitudes and direction of the energy import are close to frequency responses of tire cornering properties (TCP), which can be calculated directly according to the presented non-steady state TCP theoretical model. Selfexcited shimmy is the main type of wheel shimmy and behaves as negative equivalent damping characteristic of the tire-road vibration subsystem. The values of energy import or equivalent damping determine the tendency of wheel shimmy. Tire structural parameters have certain effects on frequency response of TCP and thereby result in influences on wheel shimmy. Based on the tire model, some valid ways to decrease shimmy tendency are concluded through proper variations of carcass stiffness, tire-width, kingpin caster, tire pneumatic trail, tire cornering stiffness and so on.

Pressure following control is the basic function of Electro-Hydraulic Braking system (EHB), which is also the key technology of stability control system and regenerative braking system for hybrid and electric vehicles. Experimental research is an important method for the control and application of EHB. This paper describes a method to test and control the EHB system through experiment on the Hardware-in-the-loop (HIL) test bench and wheel motor electric vehicle. First, the HIL test bench was established, in which the EHB was tested, including the characteristics of solenoid valves and motor. Then the wheel cylinder pressure was controlled to follow the specific signal input and the master cylinder pressure. Based on this, EHB and the pressure following control method were applied to the wheel motor electric vehicle. The results show that the braking pressure can follow the driver's braking intention to realize the conventional braking function of electric vehicles.

The poor low-temperature behavior of Li-ion batteries has limited its application in the field of electric vehicles and hybrid electric vehicles. Many previous studies concentrate on developing new type of electrolyte to solve this problem. However, according to recent research, the key limitation at low temperature is the low diffusivity of lithium ion in the anode electrodes. Hence, it is potential to study anode materials to improve low-temperature behavior of LIBs. ZnFe2O4 with higher theoretical capacity is low toxicity and abundance, contributing to its commercial application. Different ZnFe2O4 crystalline shapes have different particle sizes. Among them, the cubic ZnFe2O4 with smaller particle size will increase its own electronic and ionic conductance at lower temperature. In this regard, we evaluated low-temperature performance of LIBs with ZnFe2O4 cubes as anode materials at -25°C.