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This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

A new dynamic tire model for estimating the longitudinal/lateral road-tire friction force was derived in this paper. The model was based on the previous Dugoff tire model, in consideration of its drawback that it does not reflect the actual change trend that the tire friction force decreases with the increment of wheel slip ratio when it enters into the nonlinear region. The Dugoff model was modified by fitting a series of tire force data and compared with the commonly used Magic Formula model. This new dynamic friction model is able to capture accurately the transient behavior of the friction force observed during pure longitudinal wheel slip, lateral sideslip and combined slip situation. Simulation has been done under different situations, while the results validate the accuracy of the new tire friction model in predicting tire/road friction force during transient vehicle motion.

The accuracy of tire forces directly affects the vehicle dynamics model precision and determines the ability of the model to develop the simulation platform or design the control strategy. In the high slip angle, due to the complex interactions at tire-road interfaces, the forces generated by the tires are high nonlinearity and uncertainty, which pose issues in calculating tire force accurately. This paper presents a hybrid physical and data-driven tire force calculation framework, which can satisfy the high nonlinearity and uncertainty condition, improve the model accuracy and effectively leverage prior knowledge of physical laws. The parameter identification for the physical tire model and the data-based compensation for the unknown errors between the physical tire model and actual tire force data are contained in this framework. First, the parameters in the selected combined-slip Burckhardt tire model are identified by the nonlinear least square method with tire test data.

Transport vehicles consume a large amount of fuel with low efficiency, which is significantly affected by drivers' behaviors. An assessment system of eco-driving pattern for buses could identify the deficiencies of driver operation as well as assist transportation enterprises in driver management. This paper proposes an assessment method regarding drivers' economic efficiency, considering driving conditions. To this end, assessment indexes are extracted from driving economy theories and ranked according to their effect on fuel consumption, derived from a database of 135 buses using multiple regression. A layered structure of assessment indexes is developed with application of AHP, and the weight of each index is estimated. The driving pattern score could be calculated with these weights.

The earth's fossil energy is not limitless, and we should be taking advantage of the highly developed fields of science and technology to utilize it more efficiently and to create a fully environmentally friendly life. Considering the prodigious amount of vehicles in the world today, even a small improvement in their energy-saving performance could have a significant impact. In this paper, a new type of electro-hydraulic power steering (EHPS) system is described. It has two main advantages. First, it can significantly decrease the demand on the motor so that it can be used for a wider range of vehicles. Second, its pressure-flow characteristic can be programmed and is more flexible than hydraulic power steering (HPS) system. A prototype with a 500 W motor was applied to a truck with a front load of 2,700 kg, and static steer sweep tests were conducted to validate its feasibility.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

A high-precision steady state tire model is critical in the tire and vehicle matching research. For the moment, the popular Magic Formula model is an empirical model, which requires the pure and combined test data to identify the model parameters. Although MTS Flat-trac is an efficient tire test rig, the long test period and high test cost of a complete tire model tests for handling are yet to be solved. Therefore, it is necessary to explore a high accuracy method for predicting tire complex mechanical properties with as few test data as possible. In this study, a method for predicting tire combined slip characteristics from pure cornering and pure longitudinal test data has been investigated, and verified by comparing with the test data. Firstly, the prediction theory of UniTire model is introduced, and the formula for predicting combined slip characteristics based on constant friction coefficient is derived.

Velocity prediction on hilly road can be applied to the energy-saving predictive control of intelligent vehicles. However, the existing methods do not deeply analyze the difference and diversity of road slope driving characteristics, which affects prediction performance of some prediction method. To further improve the prediction performance on road slope, and different road slope driving features are fully exploited and integrated with the common prediction method. A rolling prediction-based multi-scale fusion prediction considering road slope transition driving characteristics is proposed in this study. Amounts of driving data in hilly sections were collected by the advanced technology and equipment. The Markov chain model was used to construct the velocity and acceleration joint state transition characteristics under each road slope transition pair, which expresses the obvious driving difference characteristics when the road slope changes.

In this paper, a sliding mode observer for estimating vehicle slip angle and tire forces is developed. Firstly, the sliding mode observer design approach is presented. A system damping is included in the sliding mode observer to speed the observer convergence and to decrease the observer chattering. Secondly, the sliding mode observer for vehicle states is developed based on a 7 DOF embedded vehicle model with a nonlinear tire model ‘UniTire’. In addition, since the tire lateral stiffness is sensitive to the vertical load, the load transfers are considered in the embedded model with a set of algebraic equations. Finally, a simulation evaluation of the proposed sliding mode observer is conducted on a validated 14 DOF vehicle model. The simulation results show the model outputs closely match the estimations by the proposed sliding mode observer.

Internal combustion engines, as the dominant power source in the transportation sector and the primary contributor to carbon emissions, face both significant challenges and opportunities in the context of achieving carbon neutral goal. Biofuels, such as biodiesel produced from biomass, and zero-carbon fuel ammonia, can serve as alternative fuels for achieving cleaner combustion in internal combustion engines. The dual-fuel combustion of ammonia-biodiesel not only effectively reduces carbon emissions but also exhibits promising combustion performance, offering a favorable avenue for future applications. However, challenges arise in the form of unburned ammonia (NH3) and N2O emissions. This study, based on a ammonia-biodiesel duel-fuel engine modified from a heavy-duty diesel engine, delves into the impact of adjustments in the two-stage injection strategy on the combustion and emission characteristics.

Using the nonlinear finite element analysis, three nonlinear characteristics of the rubber gasbag of the air spring on the bus are thoroughly analyzed, including the nonlinear characteristic of the rubber gasbag with multi layers of composite materials, the nonlinear large displacement geometry characteristic of the rubber gasbag on working, and the nonlinear contact characteristic of the rubber gasbag when contacts the pedestal and the top cover plate. A model is build and the nonlinear characteristic of the air spring on the bus is analyzed using the ABAQUS software. At last, the article discusses parameters that influence on the characteristic of the air spring for the bus.

The vehicle pull problem is very important to driving safety. Major factors that may cause the pull problem related to tire include variations of geometric dimension (e.g. RPK) and stiffness (e.g. cornering stiffness, aligning stiffness), plysteer and conicity. In previous research, the influencing mechanism of these factors was well studied. But in fact, vehicle pull problem caused by tire is probabilistic. When we assemble four tires onto the car, there could be 384 different assembly arrangements. If there are significant differences among these four tires, there will also be significant differences in the influence of different tire assembly schemes on vehicle pull, which has not been systematically discussed in previous studies. If we want to evaluate the pull performance of all these arrangements by vehicle test, it will be a time consuming process which will take almost 24 working days, along with a high test expense.

It's important to monitor the longitudinal friction at the tire/road interface for automotive dynamic control systems like ABS and ASR. Of all the tire friction models the empirical model provides a good illustration on longitudinal wheel forces. An improved exponential friction model based on vehicle driving states was proposed in this paper, the model can monitor the friction characteristics between the tire and road surface for longitudinal braking. Its validity was proven using experiments and comparison with the Pacejka Magic Formula (MF) model and others.

With the development of intelligent vehicle and active vehicle safety systems, the demand of sensors is increasing, especially in-tire sensors. Tire parameters are essential for vehicle dynamic control, including tire pressure, tire temperature, slip angle, longitudinal force, etc.. The diversification and growth of in-tire sensors require adequate power supply. Traditionally, embedded batteries are used to power sensors in tire, however, they must be replaced periodically because of the limited energy storage. The power limitation of the batteries would reduce the real-time data transmission frequency and deteriorate the vehicle safety. Heightened interest focuses on generating power through energy harvesting systems in replace of the batteries. Current in-tire energy harvesting devices include piezoelectric, electromagnetic, electrostatic and electromechanical mechanism, whose energy sources include tire deformations, vibrations and rotations.

With the development of cellular communication technology and for the sake of reducing drag resistance, the multi-lane platoon technology will be more prosperous in the future. In this article, the cooperative vehicle platoon method on the public road is represented. The method’s architecture is mainly composed of the following parts: decision-making, path planning and control command generation. The decision-making uses the finite state machine to make decision and judgment on the cooperative lane change of vehicles, and starts to execute the lane change step when the lane change requirements are met. In terms of path planning, with the goal of ensuring comfort, the continuity of the vehicle state and no collision between vehicles, a fifth-order polynomial is used to fit every vehicle trajectory. In terms of control command generation module, a model predictive control algorithm is used to solve the multi-vehicle centralized optimization control problem.

In order to predict the fatigue life of thrust rod heavy duty commercial vehicle balanced suspension, based on the continuum mechanics theory, the fatigue life prediction model of rubber with equivalent effect as damage parameter is established. Based on the equivalent stress and fatigue cumulative damage theory, the fatigue damage evolution equation of rubber material expressed by stress is derived by using the strain energy function. The general fatigue life model is established by using the maximum logarithmic principal strain as the damage parameter. The finite element model of the thrust rod is established, and the stress distribution of the spherical hinge rubber layer and the easy damage area are analyzed. Based on the equivalent stress calculation results and the axial tension stress and strain data of the rubber material, the accuracy of the results of the finite element calculation is verified.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. The mechanical properties of the bovine PAC under tensile loading have been characterized previously. However, the transverse properties of this structure, such as shear and normal traction which are equally important to understanding the skull/brain interaction under traumatic loading, have not been investigated. These material properties are essential information needed to adequately define the material model of the PAC in a finite element (FE) model of human brain. The purpose of this study was to determine, experimentally, the material properties of the PAC under normal traction loading. PAC specimens were obtained from freshly slaughtered bovine subjects from various locations.

With the rapid development of intelligent driving technology, there has been a growing interest in the driving comfort of automated vehicles. As vehicles become more automated, the role of the driver shifts from actively engaging in driving tasks to that of a passenger. Consequently, the study of the passenger experience in automated driving vehicles has emerged as a significant research area. In order to examine the impact of automatic driving on passengers' riding experience in vehicle platooning scenarios, this study conducted real vehicle experiments involving six participants. The study assessed the subjective perception scores, eye movement, and electrocardiogram (ECG) signals of passengers seated in the front passenger seat under various vehicle speeds, distances, and driving modes. The results of the statistical analysis indicate that vehicle speed has the most substantial influence on passenger perception.

The intelligent unmanned ground vehicle (UGV) motorcade system consisting of one leader and n − 1 followers is considered. The safety distance between the front and rear UGVs is treated as the control target. Since the safety distance constraint is a unilateral constraint, the state transformation is needed. Hence, a piecewise type conversion function is formulated to serve for the transformation of the original inequality constraint. The system equation is further expressed by the new state. We assume that the input of the leading UGV is known. Combined with the uncertainty evaluation, a class of collaborative controls for the following UGVs is proposed to deal with the uncertainty with unknown bound. The effectiveness of the designed control is verified by both Lyapunov stability theory and simulations. Both theoretical and simulation results illustrate that the longitudinal safety, stability and global behavior of the intelligent motorcade system are guaranteed.

The automotive industry is aggressively pursuing fuel efficiency improvements through hybridization of production vehicles, and there are an increasing number of racing series adopting similar architectures to maintain relevance with current passenger car trends. Hybrid powertrains offer both performance and fuel economy benefits in a motorsport setting, but they greatly increase control complexity and add additional degrees of freedom to the design optimization process. The increased complexity creates opportunity for performance gains, but simulation based tools are necessary since hybrid powertrain design and control strategies are closely coupled and their optimal interactions are not straightforward to predict. One optimization-related advantage that motorsports applications have over production vehicles is that the power demand of circuit racing has strong repeatability due to the nature of the track and the professional skill-level of the driver.