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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.

In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement. The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution.

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.

With the continuous popularization of electric vehicles (EVs), ensuring the best performance of EVs has become a significant concern, and lithium-ion power batteries are considered as the essential storage and conversion equipment for EVs. Therefore, it is of great significance to quickly evaluate the state of power batteries. This paper investigates a fast state estimation method of power batteries oriented to after-sales and maintenance. Based on the battery equivalent circuit model and heuristics optimization algorithm, the battery model parameters, including the internal ohmic and polarization resistance, can be identified using only 30 minutes of charging or discharging process data without full charge or discharge. At the same time, the proposed method can directly estimate the state of charge (SOC) and maximum available capacity of the battery without knowing initial SOC information.

The formation is a crucial step in the production process of lithium-ion batteries (LIBs), during which the solid electrolyte interphase (SEI) is formed on the surface of the anode particles to passivate the electrode. It determines the performance of the battery, including its capacity and lifetime. A meticulously designed formation protocol is essential to regulate and optimize the stability of the SEI, ultimately achieving the optimal performance of the battery. Current research on formation protocols in lithium-ion batteries primarily focuses on temperature, current, and voltage windows. However, there has been limited investigation into the influence of different initial pressures on the formation process, and the evolution of cell pressure during formation remains unclear. In this study, a pressure-assisted formation device for lithium-ion pouch cells is developed, equipped with pressure sensors.

The Chinese government and industries have proposed strategic plans and policies for automotive renewable-energy transformation in response to China’s commitments to peak the national carbon emissions before 2030 and to achieve carbon neutrality by 2060. We thus analyze the evolution of carbon emissions from the vehicle fleet in China with our data-driven models based on these plans. Our results indicate that the vehicle life-cycle carbon emissions are appreciable, accounting for 8.9% of the national total and 11.3% of energy combustion in 2020. Commercial vehicles are the primary source of automotive carbon emissions, accounting for about 60% of the vehicle energy cycle. Among these, heavy-duty trucks are the most important, producing 38.99% of the total carbon emissions in the vehicle operation stage in 2020 and 52.18% in 2035.

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.

Alternating current (AC) heating is an efficient and homogeneous manner to warm Lithium-ion batteries (LIBs) up. The integrated design of AC heating combined with the motor drive circuit has been studied by many scholars. However, the problems of excessive heating frequency (>1kHz) and zeros torque output of the motor during the heating process have not been solved. High-frequency AC excitation may be detrimental to the battery because the effect of high-frequency AC excitation on the state of health of the battery is unknown. In addition, although the zero-torque output can be realized by controlling the q-axis current to zero, the torque ripple is still difficult to eliminate in a real-world application. To further solve the above problems, the motor’s neutral conductor is pulled out and connected to a large capacitor to increase the current amplitude of the AC heating at low frequencies.

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.

The driving conditions of commercial logistics vehicles have the characteristics of combined urban and suburban roads with relatively fixed mileage and cargo load alteration, which affect the vehicular fuel economy. To this end, an adaptive equivalent consumption minimization strategy (A-ECMS) with vehicle speed and weight recognition is proposed to improve the fuel economy for a range-extender electric van for logistics in this work. The driving conditions are divided into nine representative groups with different vehicle speed and weight statuses, and the driving patterns are recognized with the use of the bagged trees algorithm through vehicle simulations. In order to generate the reference SOC near the optimal values, the optimal SOC trajectories under the typical driving cycles with different loads are solved by the shooting method and the optimal slopes for these nine patterns are obtained.

Battery safety issues have severely limited the rapid development and popularization of electric vehicles. Harsh conditions such as high temperature accelerate the degradation of battery safety. To address this issue, a comprehensive analysis of the impact of high-temperature cyclic aging on lithium-ion battery safety is carried out. In the Accelerating Rate Calorimeter, lithium-ion batteries are performed on adiabatic thermal runaway tests and overcharge tests. Regardless of the fully-charged state or half-charged state, in the adiabatic thermal runaway process, high-temperature cyclic aging reduces the characteristic temperature, and the activation energy from the self-heating temperature to thermal runaway triggering temperature decreases. During the overcharge process, high-temperature cyclic aging increases the voltage plateau and the crest voltage before thermal runaway, and their corresponding charging temperature decreases.

Fuel cell electric vehicles (FCEVs) require multiple components to operate properly, and the fuel cell stack—the source of power—is one of the most important components. While the number of enterprises manufacturing and selling fuel cell stacks is increasing globaly year after year, the residual challenges of core components and technologies still need to be resolved in order to keep pace with the development of lithium-ion batteries (i.e., its primary competitor). Additionally, many production and distribution standards are seen as unsettled. These barriers make large-scale commercialization an issue. Use of Proton-exchange Membrane Fuel Cells in Ground Vehicles explores the opportunities and challenges within the PEMFC industry. With the help of expert contributors, a critical overview of fuel cells and the FCEV industry is presented, and core technology, applications, costs, and trends are analyzed.

High-powered and modularity is the trend for fuel cell systems. Similar to the evolution from single-cylinder to multi-cylinder in conventional internal combustion engines, fuel cell systems shall also follow this developing process. Compared to single-stack fuel cell systems, multi-stack fuel cell systems (MFCS) can enhance the system maximum output power and improve the system performance. To achieve modular design and improve the performance of high-powered MFCS, a MFCS stacks allocation optimization algorithm based on genetic algorithms is proposed in this paper. First, remaining useful life (RUL) and efficiency are choosing as an integrated optimization index, the decision model for MFCS stacks allocation is developed. Then, a heavy-duty commercial vehicle was used as an example to match the vehicle power train parameters. The genetic algorithm is used to solve the global optimal stacks allocation scheme for the vehicle in a specific application scenario.

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).

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.

With the degradation of lithium-ion batteries, the battery safety performance changes, which further influences the safe working window. In this paper, the pouch ternary lithium-ion battery whose rated capacity is 4.2 Ah is used as the research object to investigate the impact of the high-temperature calendar and cyclic aging on tolerance performance. The overcharge-to-thermal-runaway test is performed on the fresh cell and aged cell (90% SOH). The inflection point of voltage for aged cells appears earlier than that of the fresh cell, while the voltage corresponding to the inflection point is the same for them, which means that the voltage at which lithium plating occurs is the same. However, the voltage plateau and the crest voltage before thermal runaway of aged cell are significantly higher than that of the fresh cell. Besides, ohmic heat, reversible heat, and side reaction heat make contribution to the thermal runaway triggering.

A tractor-trailer vehicle (TTV) consists of an actuated tractor attached with several full trailers. Because of its nonlinear and noncompleted constraints, it is a challenging task to avoid collisions for path planner. In this paper, we propose an efficient method to plan an optimal trajectory for TTV to reach the destination without any collision. To deal with the complicated constraints, the trajectory planning problem is formulated as an optimal control problem uniformly, which can be solved by the interior point method. A novel incremental optimization solving algorithm (IOSA) is proposed to accelerate the optimization process, which makes the number of trailers and the size of obstacles increase asynchronously. Simulation experiments are carried out in two scenarios with static obstacles. Compared with other methods, the results show that the planning method with IOSA outperforms in the efficiency.

High-nickel lithium-ion batteries extend the driving mileage of electric vehicles (EVs) to 600km without much cost increment. However, thermal accidents commonly occur due to their poor thermal stability, such as thermal runaway. To address the issue, a comprehensive analysis of the thermal runaway behavior of high-nickel lithium-ion batteries with different specifications is conducted. The thermal runaway process is divided into five stages based on self-heating generation, voltage drop, safety valve rupture, and thermal runaway triggering for the three tested cells. The three tested cells demonstrate similar behaviors during each stage of the thermal runaway process. However, there are still apparent differences between their characteristics. This study analyses the thermal runaway features from the following aspects: (i) characteristic temperature; (ii) the relationship between sudden voltage drop and characteristic temperatures; (iii) temperature recovery; (iv) thermodynamics.

In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.

From the perspective of the three elements of electromagnetic interference, the main function of shielding is to cut off the propagation path of electromagnetic noise. The battery pack casing can be regarded as shielding the electromagnetic interference conducted on its internal and external wiring harnesses, but because the battery pack casing has power lines in and out, the battery pack casing is an incomplete shield. In the field of electromagnetics, shielding can be divided into electrical shielding, magnetic shielding and electromagnetic shielding. Therefore, this paper studies its influence on the electromagnetic radiation emission of the whole vehicle from the perspective of shielding mechanism. Due to the role of the switch components in the power battery system, strong current fluctuation di/dt and voltage fluctuation dv/dt will be generated on the power cable, and these interferences will have an important impact on the radiation emission of the vehicle.