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Brake judder affects vehicle safety and comfort, making it a key area of research in brake NVH. Transfer path analysis is effective for analyzing and reducing brake judder. However, current studies mainly focus on passenger cars, with limited investigation into commercial vehicles. The complex chassis structures of commercial vehicles involve multiple transfer paths, resulting in extensive data and testing challenges. This hinders the analysis and suppression of brake judder using transfer path analysis. In this study, we propose a simulation-based method to investigate brake judder transfer paths in commercial vehicles. Firstly, road tests were conducted to investigate the brake judder of commercial vehicles. Time-domain analysis, order characteristics analysis, and transfer function analysis between components were performed.

Lightweight design is a key factor in general engineering design practice, however, it often conflicts with fatigue durability. This paper presents a way for improving the effectiveness of fatigue performance dominated optimization, demonstrated through a case study on suspension brackets for heavy-duty vehicles. This case study is based on random load data collected from fatigue durability tests in proving grounds, and fatigue failures of the heavy-duty vehicle suspension brackets were observed and recorded during the tests. Multi-objective fatigue optimization was introduced by employing multiaxial time-domain fatigue analysis under random loads combined with the non-dominated sorting genetic algorithm II with archives.

As a novel ignition technology, pre-chamber ignition can enhance ignition energy, promote flame propagation, and augment turbulence. However, this technology undoubtedly faces challenges, particularly in the context of emission regulations. Of this study, the transient characteristics of combustion and emissions in a hybrid electric vehicle (HEV) gasoline engine with active pre-chamber ignition (PCI) under the first combustion cycle of quick start are focused. The results demonstrate that the PCI engine is available on the first cycle for lean combustion, such as lambda 1.6 to 2.0, and exhibit particle number (PN) below 7×107 N/mL at the first cycle. These particles are predominantly composed of nucleation mode (NM, <50 nm) particles, with minimal accumulation mode (AM, >50 nm) particles.

The software installed in Electronic Control Units (ECUs) has witnessed a significant scale expansion as the functionality of Intelligent Connected Vehicles (ICVs) has become more sophisticated. To seek convenient long-term functional maintenance, stakeholders want to access ECUs data or update software from anywhere via diagnostic. Accordingly, as one of the external interfaces, Diagnostics over Internet Protocol (DoIP) is inevitably prone to malicious attacks. It is essential to note that cybersecurity threats not only arise from inherent protocol defects but also consider software implementation vulnerabilities. When implementing a specification, developers have considerable freedom to decide how to proceed. Differences between protocol specifications and implementations are often unavoidable, which can result in security vulnerabilities and potential attacks exploiting them.

In the process of automobile industrialization, integrated electric drive systems turn to be the mainstream transmission system of electric vehicles gradually. The main sources of noise and vibration in the chassis are from the gear reducer and motor system, as a replacement of engine. For improving the electric vehicles NVH performance, effective identification and quantitative analysis of the main noise sources are a significant basis. Based on the rotating hub test platform in the semi-anechoic chamber, in this experiment, an electric vehicle equipped with a three-in-one electric drive system is taken as the research object. As well the noise and vibration signals in the interior vehicle and the near field of the electric drive system are collected under the operating conditions of uniform speed, acceleration speed, and coasting with gears under different loads, and the test results are processed and analyzed by using the spectral analysis and order analysis theories.

To improve the prediction accuracy of the remaining useful life (RUL) of the proton exchange membrane fuel cell (PEMFC), an integrated health index (IHI) including electrical and non-electrical parameters of PEMFC is established, and the RUL prediction is conducted based on the above index. Firstly, several operating conditions including the PEMFC degradation information are selected according to the information theory method. Moreover, the IHI is established by the sequential quadratic programming method. Secondly, RUL predictions based on the power and IHI are conducted by the adaptive neuro fuzzy inference system (ANFIS), respectively. Finally, different results comparisons including power and IHI differences, differences between experimental and training/predicting results, amounts of different differences in training and predicting phases, and RUL prediction results are presented in detail.

Reinforcement learning is a promising approach to solve the energy management for hybrid electric vehicles. In this paper, based on the DQN (Deep Q-Network) reinforcement learning algorithm which is widely used at present, double DQN, dueling DQN and learning from demonstration are integrated; states, actions, rewards and the experience pool based on the characteristics of series-parallel multi-speed hybrid powertrain are designed; the hybrid energy management strategy based on D4QN (Double Dueling Deep Q-Network with Demonstrations) algorithm is established. Based on the training results of D4QN algorithm, multi-parameter analysis under state and action space, HCU (Hybrid control unit) application and MIL (Model in-loop) test research are conducted.

With the increase of motor speed and the deterioration of operating environment, it is more difficult to predict the transient temperature field (TTF). Meanwhile, it is difficult to obtain the temperature test dataset of key nodes under various complete road conditions, so the cost of bench test or real vehicle test is high. Therefore, it is of great significance to establish a high fidelity, lightweight temperature prediction model which can be applied to real vehicle thermal management for ensuring the safe and stable operation of motor. In this paper, a physical model simulating electromagnetic-heat-flow multi-physical coupling of permanent magnet synchronous motor (PMSM) in electric drive gearbox (EDG) is established, and the correctness of the model is verified by the actual EDG bench test.

In this paper, an equivalent conversion method is proposed to apply the six-dimensional force road spectrum of the four-axle vehicle on the same platform to the three-axle through the axle load comparison. Further, the feasibility of the devolved equivalent conversion method is verified, and the fatigue performance improvement of the wishbone support structure of a commercial vehicle is finally achieved. Specifically, firstly, the load spectrum at each attachment point of the suspension for the three-axle vehicle is obtained through the iteration of the multi-body dynamic model. Furthermore, the finite element model of the suspension for the three-axle vehicle is established; the analysis of fatigue life for the suspension structure is performed by extracting stress amplitude through the multi-axis cyclic counting method and calculating equivalent force amplitude through McDiarmid’s criterion, combined with the SN curve of the material.

Aiming at the laborious process in motor structure modeling for acoustic noise calculation, an improved stator structure modeling scheme is proposed, which includes stator structure simplification and equivalent material parameters identification. The stator assembly is modeled as a homogeneous solid with the same size as the stator core, and the influence of model simplification is compensated by orthotropic equivalent material parameters. The equivalent material parameters are acquired through an optimization algorithm by minimizing the error between FEM calculated modal frequencies and the modal tested results. With the stator assembly model, the motor assembly model is built, and the constrained modal characteristics of the motor assembly are verified by comparing the modal frequencies to the resonance bands in the vibration acceleration spectrum. Finally, the motor structure model is used to calculate the electromagnetic noise of an induction motor.

In this paper, the principles, advantages and disadvantages of the main technology of variable strength design of automobile B-pillar Based on the finite element simulation technology, the local stress variable strength design effect of Automobile B-pillar structure is simulated, compared and evaluated. The simulation results show that with the same mechanical properties, the overall lightweight degree of B-pillar structure with variable strength design can be reduced by about 8.9%. With the expansion of the strengthening area of variable strength design of parts, the degree of lightweight of parts can be further improved. It can be seen that the local stress variable strength design method provides a new technical option for the lightweight design of automobile parts.

Air foil bearings are gradually applied in air compressors in fuel cell vehicles for the advantages of high speed, oil-free and non-contact. Advanced air foil bearings with different structures are used to improve the performance of air compressor. Accurate modeling of the complex structures in air foil bearings has become a research hotspot in recent years. This paper presents a theoretical model for a double-top-foil air foil journal bearing (DAFJB) for centrifugal air compressors used in fuel cell vehicles. The foil structure is modeled by finite element method (FEM) using shell elements. Coulomb law and penalty function method are applied to model the tangential and normal behavior of the contact areas. The local contact between the middle top foil and the bump foil, the bump foil and the bearing sleeve are modeled using node-to-segment contact method. The large-area contact behavior between two layers of top foils is modeled by simplified surface-to-surface contact scheme.

The fuel-saving potential of a series hybrid electric vehicle (SHEV) was investigated in this work based on the future goals and technical roadmaps proposed by China's automobile and internal combustion engine (ICE) industry. The genetic algorithm optimization method and dynamic programming energy management strategy are used to optimize the key component parameters of a typical SHEV SUV to improve the fuel economy of the vehicle. Results showed that the fuel consumption of the vehicle would be 3.24 L / 100km in 2035, which is 37.21% less than 5.16 L / 100km in 2020, following the industries’ roadmaps. The results also indicated that the improvement of the ICE’s thermal efficiency is the main reason for the decrease of the vehicle’s fuel consumption. In addition, the improvement of working points and the reduction of energy losses of the key components also contribute to the improvement of the fuel economy.

SEAT Department of SAIC Motor Vehicle Company starts innovatively applying the single motor and P2.5 configuration scheme from EDU G2(Electric Drive Unit Generation 2), which consists of six engine gears and four motor gears. EDU G2 is very compact and adaptable through the coupling design. Gear coupling make the engine and motor coordination limited, so as to the high efficiency zone of the engine and the high efficiency zone of the motor cannot match in some working conditions, which affect the performance of the vehicle. Therefore, SEAT developed the second generation of single-motor plug-in hybrid system EDU G2 Plus EDU G2(Electric Drive Unit Generation 2 Plus), which realized the decoupling design of 5 engine gears and 2 motor gears, so that the power output of engine and motor is freely. With excellent power and economic performance, the vehicle has been well received by customers.

The application of Li(Ni0.8Co0.1Mn0.1)O2 (NCM811) cathode-based lithium-ion batteries (LIBs) has alleviated electric vehicle range anxiety. However, the subsequent thermal safety issues limit their market acceptance. A detailed analysis of the failure evolution process for large-format LIBs is necessary to address the thermal safety issue. In this study, prismatic cells with nominal capacities of 144Ah and 125Ah are used to investigate the thermal runaway (TR) characteristics triggered by lateral overheating. Additionally, TR characteristics under two states of charge (SoCs) (100% and 5%) are discussed. Two cells with 100% SoC exhibit similar characteristics, including high failure temperature, high inhomogeneity of temperature distribution, multi-points jet fire, and significant mass loss. Two cells with 5% SoC demonstrate only a slight rupture of the safety valve and the emission of white smoke.

As a prerequisite for energy management of hybrid vehicles, the results of speed prediction can optimize the performance of vehicles and improve fuel efficiency. Energy management strategies are usually developed based on standard driving cycles, which are too generalized to show the variability of driving conditions in different time and locations. Therefore, this paper constructs a representative driving cycle based on driving data of the corresponding time and location, used as historical information for prediction. We propose a method to construct the driving cycle based on Markov chain theory before constructing the prediction model. In this paper, multiple prediction methods are compared with traditional parametric methods. The difference in prediction accuracy between multiple prediction methods under the single time scale and multiple time scale were compared, which further verified the advantages of the speed prediction method based on Markov chain theory.

Calculating accurately iron bridge saturation effects of the magnetic field, for Permanent Magnet Assisted Synchronous Reluctance Motors (PMASynRMs), remains to be a knotty problem. This paper presents an analytical modeling method to predict open-circuit magnetic field distributions and electromagnetic performances of PMASynRMs, considering iron bridge saturation effects. This analytical modeling method combines the magnetic equivalent circuit method, superposition principle, the solution of the governing Maxwell’s field equations and a complex relative permeance function. A quadruple-layer PMASynRM are remodeled into four surface-inserted permanent magnet synchronous motors (SPMSMs) which have different surface-inserted permanent magnets.

The separation and analysis of the torque of the permanent magnet synchronous motor is of great significance for optimizing the torque output of the motor. Based on the frozen permeability method, the virtual work principle (VWP) or the Maxwell stress tensor method (MSTM) is often used to separate the torque for torque analysis. However, considering the influence of non-ideal factors such as motor saturation, cross-coupling and flux harmonics, there are differences in torque separation between the VWP and the MSTM, which has been researched and analyzed in this paper. Based on this, for the assisted airspace barrier design of a surface-inserted permanent magnet synchronous motor, to conduct theoretical research on the torque optimization design, this paper uses the VWP to separate the average torque and the MSTM to separate the torque ripple.

An accurate finite element (FE) model is the basis for the numerical prediction of vibration and noise of permanent magnet synchronous motors (PMSMs). This paper provides an equivalent modeling method of PMSMs considering the orthotropic material parameters of the stator system. First, a theoretical analysis of the influence of orthotropic material parameters on modal characteristics is implemented. Subsequently, the influence of orthotropic material parameters on the modal frequency of the stator is analyzed through the FE method. Then, the modal parameters of the stator core and the stator assembly are obtained by modal tests. According to the equivalent FE model and modal parameters, the orthotropic material parameters of the stator system are acquired. Moreover, to save the calculation time and simplify the modal identification process, the influence of windings is taken into account through additional mass and additional stiffness during the modeling process.

As the international community strengthens the control of carbon dioxide emissions, electric vehicles have gradually become a substitute for internal combustion engine vehicles. The battery pack is one of the most important components of electric vehicles. The strength and fatigue performance of the battery support plate not only affect the performance of the vehicle but also concern the safety of the driver. In the present study, the finite element model of a battery pack for fatigue analysis is completely established. The random vibration stress response analysis and acceleration power spectral density response analysis of the support plate for the battery pack are carried out, and the accuracy of the finite element model is verified by a random vibration test.