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As the main power source of new energy vehicles, the durability and fatigue characteristics of the battery pack directly affect the performance of the vehicle. The battery pack system was modelled using multi-body dynamics software, with 7 and 13 degree of freedom models developed. Using the established model, the intrinsic properties of the battery pack are computationally analyzed. To calculate the dynamic characteristics, a sinusoidal displacement excitation is applied to the wheel centre of mass, and the displacement and acceleration of the battery pack centre of mass are calculated for both models.The displacement and acceleration curves at the centre of mass of the battery pack of the two models are compared. The results show that the amplitude of the displacement and acceleration curves at the centre of mass of the 13 degrees of freedom model of the battery pack has decreased significantly.

To reduce the heating energy consumption of electric vehicles in winter, a switching control strategy for multiple heating modes formed by three heat sources, including air, motor waste heat, and positive temperature coefficient (PTC) heaters, is designed. Firstly, an integrated thermal management system (ITMS) simulation model for the heat pump air conditioning system, battery thermal management system, and motor thermal management system is established based on the AMESim software. Secondly, the influence of ambient temperature and motor outlet coolant temperature on the heating performance of three cabin heating modes is studied. Specifically, the three cabin heating modes include the pure motor waste heat source heat pump mode, the pure air-source heat pump mode, and the dual heat source heat pump mode with waste heat source and air source. Based on the analysis results, the opening and closing strategies for the three cabin heating modes are discussed.

Battery Run-down under the Electric Vehicle Operation (BREVO) model is a model that links the driver’s travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. This study implements reinforcement learning (RL) to the simplified BREVO model to optimize drivers’ decisions on charging such as charging rate, charging time, and charging capacity needed. This is done by a reward function that considers both the driver’s daily travel demands and the minimization of battery degradation over a year. It shows that using appropriate charger type (No Charge, Level 1, Level 2, direct-current Fast Charge [DCFC], extreme Fast Charging [xFC]) with an appropriate charging time can reduce battery degradation and total charging cost at the end of the year while satisfying driver’s daily travel demand.

A liquid-cooled plate is an important component for cooling batteries inside a battery package system. The structure of the liquid-cooling plate significantly affects the temperature conditions of power batteries and the energy consumption of the liquid-cooling system. However, there is a lack of precise knowledge regarding the specific factors that contribute to these impacts. In this study, the influence of structural parameters of flow channel on the heat dissipation performance is studied to solve above problems. A test bench for measuring battery pack cooling performances was built, and pressure drop of liquid-cooled plate and maximum temperature of battery were measured. A CFD model for liquid-cooled plate performance calculations was developed. Using the established model, pressure drop, and maximum temperature were calculated. The measured data are compared with the calculated date, which validate the proposed model.

The influence of the channels of a liquid-cooled plate on the heat dissipation performance of battery module is investigated in this paper. A topology optimization method for obtaining channel configurations of the liquid cooled plate is presented. Firstly, the battery pack cooling system test platform is built to test the flow resistance of the liquid-cooled plate under different flow rates and the maximum temperature and temperature difference of the battery under different working conditions. Secondly, the geometric model of the battery pack is established, and CFD software is used to simulate according to the test conditions. The test results validate the correctness of the model. Then, taking the average surface temperature of the liquid-cooled plate as the optimization objective, the topology optimization structure of the liquid-cooled plate is obtained by variable density method.

This paper presents an adaptive H2/H∞ control strategy for a semi-active suspension system with unknown suspension parameters. The proposed strategy takes into account the damping force characteristics of continuous damping control (CDC) damper. Initially, the external characteristics of CDC damper were measured, and a forward model and a back propagation (BP) neural network inverse model of CDC damper were proposed using the measured data. Subsequently, a seven-degree-of-freedom vehicle with semi-active suspension system and H2/H∞ controller was designed. Multiple feedback control matrices corresponding to different sprung mass parameter values were determined by analyzing time and frequency domain performance. Finally, a dual observer system combining suspension state and parameter estimation based on the Kalman filter algorithm was established.

Tortuosity, viscous characteristic length and thermal characteristic length are three important parameters for estimating the acoustic performance of porous materials, and it is usually measured by ultrasonic measurement technology, which is costly. In this paper, a method for identifying the tortuosity, viscous characteristic length and thermal characteristic length for the porous fiber materials mixed with kapok fiber and two kinds of other fiber materials is proposed. The tortuosity is calculated by using the porosity and high-frequency normal sound absorption coefficient of porous materials. According to the normal sound absorption coefficient curve of porous materials under plane wave incidence, viscous characteristic length and thermal characteristic length are identified through the Johnson-Champoux-Allard-Lafarge (JCAL) model and genetic algorithm by using the measured parameters, the calculated tortuosity and static thermal permeability.

As an important vibration damping element in automobile, the rubber mount can effectively reduce the vibration transmitted from the engine to the frame. In this study, a method of parameters identification of Mooney-Rivlin model by using surrogate model was proposed to more accurately describe the mechanical behavior of mount. Firstly, taking the rubber mount as the research object, the stiffness measurement was carried out. And then the calculation model of the rubber mount was established with Mooney-Rivlin model. Latin hypercube sampling was used to obtain the force and displacement calculation data in different directions. Then, the parameters of the Mooney-Rivlin model were taken as the design variables. And the error of the measured force-displacement curve and the calculated force-displacement curve was taken as the system response. Two surrogate models, the response surface model and the back-propagation neural network, were established.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

Taking a closed airbag suspension system as studying objects, the nonlinear dynamic model of the reservoir, compressor, solenoid valve, pipeline and air spring is established. The compressor exhaust volume, solenoid valve flow rate and air spring charging and discharging rate are calculated and compared with experiment to validate the model. Taking pressure difference and height adjustment rate under different working conditions of an airbag suspension as control measures, a control strategy is developed based on the established nonlinear dynamic model. The result indicates that when the vehicle is in curb weight, design weight and GVW (gross vehicle weight), the working time of the compressor can be reduced by 13.6%, 15.1% and 46.5%, respectively, compared with the conventional mode, during a height adjustment cycle. Then a state observer is proposed to estimate the steady-height for reducing the disturbance of measured height from road excitation.

A battery cooling system model of electric vehicle was established. The system model consists of a battery pack, a pump, a radiator, and a fan. A cooling plate was used to cool the battery pack, and the coolant flow rate in the cooling plate was controlled by the pump. The heat in the battery cooling system was released into the ambient air through the radiator. A finite element analysis model of the cooling plate was established to calculate the pressure drop of the cooling plate. A coupled dynamics model of the battery pack-radiator cooling system was established to simulate the temperature of the battery pack during charging and discharging. Tests were carried out to obtain the pressure drop of the cooling plate and the temperature of the battery pack under different working conditions. The simulation results and test results were compared and analyzed, and the accuracy of the models were verified.

Electric vehicle battery thermal management based on liquid cooling is the mainstream form of cooling for new energy vehicles. According to energy consumption, the system is divided into active cooling system and passive cooling system. The cooling of battery modules in these two cooling systems is carried out by liquid-cooled plate, which is connected in series in the cooling system. Therefore, the design of the liquid-cooled plate has a great impact on the effect of battery heat dissipation. In this paper, considering the advantages of existing liquid-cooled plates, the author proposed a series-parallel hybrid dc channel liquid-cooled plate structure, taking square lithium iron phosphate battery pack as the research object. Finally, the effects of different inlet flows and temperatures of the liquid-cooled plate on the thermal performance of the liquid-cooled plate were investigated by using single factor analysis.

In the manufacturing of battery boxes using the aluminum extruded process, poor consistency of products and a short life of the die for making aluminum structural sections are usually observed. A new method of producing battery boxes is proposed that combines steel stamped and aluminum extruded process. This paper first describes the design requirements for a battery box using a new process, and several important issues such as weld seam arrangement and error proofing in the manufacturing process are discussed. To address the issue of weld seam arrangement, the following three principles should be considered in the design: These principles include that the profile lap angle should be above 90°, three or more beams should not be lapped too closely together, and multiple brackets in close proximity should be designed as one unit.

Air springs with auxiliary chambers (ASAC) are widely used in automotive suspension systems. The introducing of the auxiliary chamber and the connecting flow passage makes the system more complex, especially in which case an additional resonance peak caused by the air inertia in a connecting pipe appears. To characterize the nonlinear dynamic characteristics, this paper proposes a novel physical-neural network hybrid modeling method for ASACs. Firstly, experiments are carried out to measure the dynamic characteristics of ASACs. Then, based on the thermodynamic principle, a nonlinear dynamic characteristic model for the ASAC is developed and a linearized process is performed to obtain a linearized physical model. Due to the amplitude dependence and frequency dependence in the dynamic characteristics of ASACs, the physical model cannot accurately characterize these nonlinearities.

A common scenario in engineering design is the evaluation of expensive black-box functions: simulation codes or physical experiments that require long evaluation times and/or significant resources, which results in lengthy and costly design cycles. In the last years, Bayesian optimization has emerged as an efficient alternative to solve expensive black-box function design problems. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition functions that drives the design process. Successful Bayesian optimization strategies are characterized by accurate surrogate models and well-balanced acquisition functions. The Gaussian process (GP) regression model is arguably the most popular surrogate model in Bayesian optimization due to its flexibility and mathematical tractability. GP regression models are defined by two elements: the mean and covariance functions.

Robust data association is a core problem of visual odometry, where image-to-image correspondences provide constraints for camera pose and map estimation. Current state-of-the-art visual semantic odometry uses local map points semantics, building semantic residuals associated with all classes to realize medium-term tracking of points. Considering the problem of inefficient semantic data associations and redundant semantic observation likelihood model in the visual semantic odometry, we propose a visual odometry, Local Semantic Odometry (LVSO), which is integrated with medium-term semantic constraints based on local nearest neighbor distance model.

As the power of electric vehicles (EVs), lithium-ion batteries (LIBs) are subjected to a variety of mechanical loads during electrochemical operation. Under this operating environment, lithium-ion batteries are at risk of internal short circuit, thermal runaway and even fire, threatening the safety of electric vehicles. The purpose of this paper is to investigate the mechanical behaviors and failure mechanisms of the battery separator to improve the safety of lithium-ion batteries under mechanical loads. In this study, uniaxial tensile, through-thickness compression and biaxial punch tests were performed to characterize two types of separators, dry-processed polypropylene (PP) separators and wet-processed ceramic-coated separators, and to analyze and compare their mechanical properties and failure modes. The comprehensive mechanical tests show that the failure modes of the different separator types are different, with the more anisotropic separator having more complex failure modes.

Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme.

Electromagnetic semi-active hydraulic engine mount (HEM) with double inertia tracks can realize the opening and closing of the inertia tracks through the control of electromagnetic actuator, so as to meet the needs of vibration isolation in different working conditions, but the cost is high. In this paper, without using electromagnetic actuator, a mechanical semi-active HEM with double inertia tracks is designed and manufactured with simple structure and low cost. In this study, the feature of mechanical semi-active HEM with double inertia tracks is that a baffle-current limiting column structure is added in the inertia track. Under different excitation amplitudes, the baffle-current limiting column structure can open and close the inertia track passively. Several mechanical semi-active HEM with double-inertia tracks samples and conventional inertia tracks HEM samples are manufactured and the dynamic characteristics of these samples under low frequency excitation are tested.

The vehicle will produce certain shock and vibration during the braking process, which will affect the driving experience of the driver. Aiming at the problems of pitch vibration, longitudinal vibration and shock during the braking process, this paper proposes a planning and following control method for target longitudinal acceleration in post-braking phase, and designs control trigger strategies. Target longitudinal acceleration planning takes minimizing longitudinal shock as the design goal. The following control takes the brake pressure as the control object, and adopts the “feedforward +PID feedback” method to follow the target longitudinal acceleration. Besides, considering the safety of braking process, the trigger condition of control is designed which utilizes BP neural network method to judge whether the control has to be triggered. Based on Simulink software, the simulation model of straight-line braking is established.