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The analysis of nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. In this paper, a physics-based model of a Ni-MH battery will be presented. To analyze its performance, the efficiency of the battery is chosen as the performance measure, which is defined as the ratio of the energy output from the battery and the energy input to the battery while charging. Parametric sensitivity analysis will be used to generate sensitivity information for the state variables of the model. The generated information will be used to showcase how sensitivity information can be used to identify unique model behavior and how it can be used to optimize the capacity of the battery. The results will be validated using a finite difference formulation.

Modelling of disc in brake squeal analysis is complicated because of the rotation of disc and the sliding contact between disc and pads. Many analytical or analytical numerical combined modeling methods have been developed considering the disc brake vibration and squeal as a moving load problem. Yet in the most common used complex eigenvalue analysis method, the moving load nature normally has been ignored. In this paper, a new modelling method for rotating disc from the point of view of modal is presented. First finite element model of stationary disc is built and modal parameters are calculated. Then the dynamic response of rotating disc which is excited and observed at spatial fixed positions is studied. The frequency response function is derived through space and time transformations. The equivalent modal parameter is extracted and expressed as the function of rotation speed and original stationary status modal parameters.

The study and prevention of unstable vibration is a challenging task for vehicle industry. Improving predicting accuracy of braking squeal model is of great concern. Closed-loop coupling disc brake model is widely used in complex eigenvalue analysis and further analysis. The coupling stiffness of disc rotor and pads is one of the most important parameters in the model. But in most studies the stiffness is calculated by simple static force-deformation simulation. In this paper, a closed-loop coupling disc brake model is built. Initial values of coupling stiffness are estimated from static calculation. Experiment modal analysis of stationary disc brake system with brake line pressure and brake torques applied is conducted. Then an optimization process is initiated to minimize the differences between modal frequencies predicted by the stationary model and those from test. Thus model parameters more close to reality are found.

In the face of energy and environmental problems, how to improve the economy of fuel cell vehicles (FCV) effectively and develop intelligent algorithms with higher hydrogen-saving potential are the focus and difficulties of current research. Based on the Toyota Mirai FCV, this paper focuses on the short-term speed prediction algorithm based on the back propagation neural network (BP-NN) and carries out the research on the short-term speed prediction algorithm based on BP-NN. The definition of NN and the basic structure of the neural model are introduced briefly, and the training process of BP-NN is expounded in detail through formula derivation. On this basis, the speed prediction model based on BP-NN is proposed. After that, the parameters of the vehicle speed prediction model, the characteristic parameters of the working condition, and the input and output neurons are selected to determine the topology of the vehicle speed prediction model.

The performance, life cycle cost, and safety of electric and hybrid electric vehicles (EVs and HEVs) depend strongly on their energy storage system. Advanced batteries such as lithium-ion (Li-ion) polymer batteries are quite viable options for storing energy in EVs and HEVs. In addition, thermal management is essential for achieving the desired performance and life cycle from a particular battery. Therefore, to design a thermal management system, a designer must study the thermal characteristics of batteries. The thermal characteristics that are needed include the surface temperature distribution, heat flux, and the heat generation from batteries under various charge/discharge profiles. Therefore, in the first part of the research, surface temperature distribution from a lithium-ion pouch cell (20Ah capacity) is studied under different discharge rates of 1C, 2C, 3C, and 4C.

As mechanical damage induced thermal runaway of lithium-ion batteries has become one of the research hotspots, it is quite crucial to understand the mechanical behavior of component materials of lithium battery. This study focuses on the mechanical performance of separators and electrodes under different loading conditions and the error sources analysis for test results. Uniaxial tensile tests were conducted under both quasi-static and dynamic loading conditions. The strain was acquired through the combination of high speed camera and digital image correlation (DIC) method while the force was obtained with a customized load cell. Noticeable anisotropy and strain rate effect were observed for separators. The fracture mode of separators is highly correlated to the microscopic fiber orientation. To demonstrate the correlation microscopic images of separator material were obtained through SEM to match the facture edges of tensile tests at different loading directions.

Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.

As a novel assist actuator of brake system, the electromechanical brake (EMB) booster has played a significant role in the battery electric vehicles and automatic driving vehicles. It has advantages of independent to vacuum source, active braking, and tuning pedal feeling compared with conventional vacuum brake booster. In this article, a novel EMB booster system is proposed, which is consisted of a permanent magnet synchronous motor (PMSM), a two-stage reduction by gears and ball screw, a servo body, and a reaction disk. Together with the hydraulic control unit, it has two working modes: active braking for automatic drive and passive braking for driver intervention. The structure and work principle of the electric brake booster system is first introduced. The precise control from pedal force to hydraulic pressure is the key for such a power-assisted brake actuator. We translate the control problem of force feedback control to position tracking control.

In this article, the regenerative braking system is designed, which can realize the torque allocation between electric braking and hydraulic braking, where the cost function designed in this article considers factors of braking torque following effect, energy regenerative power, and hydraulic braking consumed power. In addition, a complete anti-lock braking system (ABS) is designed, which is based on regenerative braking. With the optimal slip ratio as control target, target wheel speed, control wheel speed, braking torque control strategy, and enable/disenable control logic of ABS are determined. By MATLAB/Simulink-DYNA4 co-simulation and real vehicle test, the feasibility and applicability of ABS based on regenerative braking are verified, under the condition of small severity of braking.

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.

Proper tire pressure is very important for multiple driving performance of a car, and it is necessary to monitor and warn the abnormal tire pressure online. Indirect Tire Pressure Monitoring System (TPMS) monitors the tire pressure based on the wheel speed signals of Anti-lock Braking System (ABS). In this paper, an indirect TPMS method is proposed to estimate the tire pressure according to its resonance frequency of circumferential vibration. Firstly, the errors of ABS wheel speed sensor system caused by the machining tolerance of the tooth ring are estimated based on the measured wheel speed using Recursive Least Squares (RLS) algorithm and the measuring errors are eliminated from the wheel speed signal. Then, the data segments with drive train torsional vibration are found out and eliminated by the methods of correlation analysis.

Metal foil is a widely used material in the automobile industry, which not only is the honeycomb barrier material but is also used as current collectors in Li-ion batteries. Plenty of studies proved that the mechanical property of the metal foil is quite different from that of the metal sheet because of the size effect on microscopic scale, as the metal foil shows a larger fracture stress and a lower ductility than the metal sheet. Meanwhile, the fracture behavior and accurate constitutive model of the metal foil with the consideration of the strain rate effect are widely concerned in further studies of battery safety and the honeycomb. This article conducted experiments on 8011H18 aluminum foil, aiming to explore the quasi-static and dynamic tension testing method and the anisotropic mechanical behavior of the very thin foil. Two metal foil dog-bone specimens and three types of notched specimens were tested with a strain rate ranging from 2 × 10−4/s to 40/s and various stress states.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Plug-in electric vehicle (PHEV) has a promising prospect to reduce greenhouse gas (GHG) emission and optimize engine operating in high-efficiency region. According to the maximum electric power and all-electric range, PHEVs are divided into two categories, including “all-electric PHEV” and “blended PHEV” and the latter provides a potential for more rational energy distribution because engine participates in vehicle driving during aggressive acceleration not just by motor. However, the frequent use of engine may result in severe emissions especially in low state of charge (SOC) and ahead of catalyst light-off. This study quantitatively investigates the impact of oil viscosity and driving mode (hybrid/conventional) on oil dilution and emissions including particle number (PN).

Studying drifting dynamics and control could extend the usable state-space beyond handling limits and maximize the potential safety benefits of autonomous vehicles. Distributed electric vehicles provide more possibilities for drifting control with better grip and larger maximum drift angle. Under the state of drifting, the distributed electric vehicle is a typical nonlinear over-actuated system with actuator redundancy, and the coupling of input vectors impedes the direct use of control algorithm of upper. This paper proposes a novel automated drifting controller for the distributed electric vehicle. First, the nonlinear over-actuated system, comprised of driving system, braking system and steering system, is formulated and transformed to a square system through proposed integrative recombination method of control channel, making general nonlinear control algorithms suitable for this system.

A novel fault tolerant brake strategy for In-wheel motor driven electric vehicles based on integral sliding mode control and optimal online allocation is proposed in this paper. The braking force distribution and redistribution, which is achieved in online control allocation segment, aim at maximizing energy efficiency of the vehicle and isolating faulty actuators simultaneously. The In-wheel motor can generate both driving torque and braking torque according to different vehicle dynamic demands. In braking procedure, In-wheel motors generate electric braking torque to achieve energy regeneration. The strategy is designed to make sure that the stability of vehicle can be guaranteed which means vehicle can follow desired trajectory even if one of the driven motor has functional failure.

In low-temperature environment, heat supply requires considerable energy, which significantly increases energy consumption and shortens the mileage of electric vehicle. In the fuel cell vehicles, waste heat generated by the fuel cell system can supply heat for vehicle. In this paper, a thermal management system is designed for a the fuel cell interurban bus. Thermal management strategy aiming at temperature regulation for the fuel cell stack and the passenger compartment and minimal energy consumption is proposed. System model is developed and simulated based on AMESim and Matlab/Simulink co-simulation. Simulation results show that the fuel cell system can provide about 78 % energy of maximum heat requirement in -20 °C ambient temperature environment.

The vision for the future automotive chassis is to interconnect the lateral, longitudinal, and vertical dynamics by separately controlling driving, braking, steering, and damping of each individual wheel. A major advantage of all wheel drive electric vehicles with four in-wheel motors is the possibility to control the torque and speed at each wheel independently. This paper proposes a traction controller for such a vehicle. It estimates the road's adhesion potential at each wheel and adjusts each motor voltage, such that the longitudinal slip is kept in an optimal range. For development and validation, a full vehicle model is designed in ADAMS/View software, in co-simulation with motor and control elements, modeled in MATLAB/Simulink.

Vehicle needs suspension and steering systems with different features to fit different driving conditions. In normal straight driving condition, soft suspension and heavy steering systems are needed to achieve better ride comfort and straight line driving stability; in turning conditions, hard suspension and lightweight steering systems are needed to get better handing stability. The semi-active suspension system with Magneto-Rheological dampers can improve the ride comfort and handling performance of vehicle. Electrical power steering system is developed rapidly due to its portable and flexible operations as well as stable steering performance.

The new control algorithm for parallel hybrid electric vehicle is presented systematically, in which engine operation points are limited within higher efficient area by the control algorithm and the state of charge (SOC) is limited in a range in order to enhance the batteries' charging and discharging efficiency. In order to determine the ideal operating point of the vehicle's engine, the control strategy uses a lookup table to determine the torque output of the engine. The off-line simulation model of parallel HEV power train is developed which includes the control system and controlled objective (such as engine, electric motor, battery pack and so on). The results show that the control algorithm can effectively limite engine and battery operation points and much more fuel economy can be achieved than that of conventional one.