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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.

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.

In the paper, the kinematics model and a mathematical optimization model for the multi-axle steering system of heavy-duty vehicle are established based on the mechanism kinematics analysis. A new weight function is designed considering the probability of steering angle. Takes 10×8 heavy-duty vehicle as an example, the parameters of multi-axle steering system are optimized. The result shows that the result with weight function has better effect than other conditions. We also develop mechanism kinematics analysis and simulation software. The work in the paper will help to guide the design of steering system of multi-axle steering heavy-duty vehicle.

In this paper, a parasite system power empirical model of a PEM fuel cell engine suitable for the study of fuel cell vehicle simulation is developed by fitting the experimental data with quadratic polynomial. The assumption of the model is that the fuel cell stack is in steady-state condition. The properties of the parasite system power are analyzed. Based on the analysis of the properties of the parasite power, two parameters--- stack power factor RAS and FCE power factor RAF are introduced to evaluate the quality of the stack and the fuel cell engine. Moreover, the parasite system power model is verified by test data. The result indicates that the model is accurate to reflect the static performance of the parasite system. The advantage of the model is that its structure is simple, and its parameters are easy to be obtained. It is easy to apply to the study of fuel cell vehicle simulation.

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.

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.

In this paper, a hydrogen consumption rate model of a PEM fuel cell engine is developed based on experimental data. The assumption of the model is that fuel cell stack works in steady-state condition. The relationships between the hydrogen consumption rate and stack current, stack power and Fuel Cell Engine (FCE) power are analyzed. Based on the hydrogen consumption rate model, a hydrogen specific consumption model is developed. Moreover, the models presented in this paper are verified by test data. The results indicate that these models are accurate to reflect the static performance of fuel cell stack and fuel cell engine. The advantages of these models are that theirs structures are very simple, and theirs parameters are easy to be obtained. They are easy to be applied to the study of fuel cell vehicle simulation.

Fuel cell vehicle commercialization and mass production are challenged by the durability of fuel cells. In order to research the durability of fuel cell stack, it is necessary to carry out the related durability test. The performance prediction of fuel cell stack can be based on a short time durability test result to accurately predict the performance of the fuel cell stack, so it can ensure the timeliness of the test results and reduce the cost of test. In this paper, genetic algorithm-BP neural network (GA-BPNN) is proposed to modeling automotive fuel cell stack to predict the performance of it. Based on the strong global searching ability of genetic algorithm, the initial weights and threshold selection of neural networks are optimized to solve the shortcoming that the random selection of the initial weights and thresholds of BP neural network which can easily lead to the local optimal value.

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.

The vehicular fuel cell stack is unavoidably impacted by the vibration in the real-world usage due to the road unevenness. However, effects of vibration on stacks have yet to be completely understood. In this work, the mechanical integrity and gas-tightness of the stack were investigated through a strengthen road vibration test with a duration of 200 h. The excitation signals applied in the vibration test were simulated by the acceleration of the stack, which were previously measured in a vehicle vibration test. The load signals of the vehicle vibration test were iterated through a road simulator from vehicle acceleration signals which were originally sampled in the proving ground. Frequency sweep test was conducted before and after the vibration test. During the vibration test, mechanical structure inspection and pressure maintaining test of the stack were conducted at regular intervals.

Durability performance prediction is a critical issue in fuel cell research. During the demonstration operation of fuel cell commercial vehicles in China, this issue has attracted more attention. In this article, the long short-term memory neural network (LSTMNN), which is an improved recurrent neural network (RNN), and the demonstration operation data are used to establish the prediction model to predict the durability performance of the fuel cell stack. Then, a model based on a back-propagation neural network (BPNN) is established to be a control group. The demonstration operation data is divided into training group and validation group. The former is used to train the prediction model, and the latter is used to verify the validity and accuracy of the prediction model. The outputs of the prediction model, as the durability performance evaluation indexes of the fuel cell, are the polarization curve (current-voltage curve) and the voltage decay curve (time-voltage curve).

The behavior of driver course decision making is analyzed with the theory of system fuzzy decision making, and some factors that influence this behavior are studied also. Based on these, a fuzzy decision making model of driver dynamically determining vehicle preview course is given. This model can simulate the driver's control behavior of deciding the vehicle preview course in the process of driver handling the vehicle, based on the feasible region of front road. Taking advantage of fuzzy decision making theory's character, the model can describe many decision criteria such as driving safety, driving handiness and driving legality. The simulation results show that the model can be directly applied into the simulation of driver-vehicle-road closed-loop system and the research of intelligent vehicle.

A long vehicle is more difficult to drive than a short one, but the mechanism of this phenomenon is still ambiguous. This paper will devote main effort to elaborate this phenomenon based on the theory of preview-follower driver model. Drivers always hope that the vehicle center can travel according to a predetermined trajectory. However, there is often a deviation between the vehicle center predicted by the driver and the actual center. As for this phenomenon, a conception of driver preview eccentricity is proposed. In order to analyze the influence of the proposed conception on vehicle driving track, a multi-axle steering vehicle model is built and some basic expressions of important parameters are deduced from this model firstly. Then, the developmental driver model with the factor of preview eccentricity based on preview-follower theory is established in the state of low velocity quasi-static. Subsequently, this model for long vehicles is extended to a dynamic driver model.

This paper presents a general kinematical model for all variety of leaf springs, including traditional laminated, asymmetrical, and tapered leaf springs, to calculate the longitudinal and winding deformations of axles during bouncing, braking and traction, which may introduce additional steering effects or variations of roll-steer property of a vehicle. Some experiments were introduced to verify the model. Accordingly, braking performance of a light truck has been improved.

With the development of the advanced driver assistance system and autonomous vehicle techniques, a precise description of the driver’s steering behavior with mathematical models has attracted a great attention. However, the driver’s steering maneuver demonstrates the stochastic characteristic due to a series of complex and uncertain factors, such as the weather, road, and driver’s physiological and psychological limits, generating negative effects on the performance of the vehicle or the driver assistance system. Hence, this paper explores the stochastic characteristic of driver’s steering behavior and a novel steering controller considering this stochastic characteristic is proposed based on stochastic model predictive control (SMPC). Firstly, a search algorithm is derived to describe the driver’s road preview behavior.

Vehicle handling and stability performances are greatly determined by non-steady state (NSS) tire cornering properties. Analytical derivation of NSS tire cornering models are presented in this paper based on Pacejka's string-concept assumption, in which carcass is assumed to be a stretched string with lateral deformation and lateral relaxation. The lateral inputs of the models are either displacement-based (lateral displacement and yaw angle) or slip-based (slip angle and turn slip). The transient deformations in spatial domain in both longitudinal and lateral directions are obtained directly from geometric relationship of contact patch. The additional self-aligning moment due to longitudinal deformation of contact patch after effect of tire width is considered is also achieved according to geometric relationship of contact patch in longitudinal direction and two transient geometric conditions of contact point.

Non-steady state (NSS) tire cornering properties show obvious differences from steady state (SS) tire cornering properties. A two-DOF automobile model with steer angle as an input is established based on the known NSS tire model considering complex carcass deformation. The tire model can certainly be applied to modelling of a multi-DOF automobile system. The frequency responses of lateral acceleration and yaw rate are then derived. An evaluation index, amplitude-frequency characteristic of relative error (AFCRE), is used to analyze the influences of NSS front wheels (FW) and/or rear wheels (RW) on automotive handling. The influences of NSS FW are much greater than those of NSS RW only on automotive handling. The established automobile model can also be applied to other similar studies of vehicle dynamics.