Vehicle Manufacturers Research Articles

Quantifying Volume Change in Porous Electrodes Via the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, the need for coupled electrochemical/mechanical models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary[1-8]. In this study, we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge[9-14] and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions. References T. R. Garrick, K. Kanneganti, X. Huang and J. W. Weidner, J Electrochem Soc, 161, E3297 (2014).T. R. Garrick, Y. Dai, K. Higa, V. Srinivasan and J. W. Weidner, Ecs Transactions, 72, 11 (2016).T. R. Garrick, K. Higa, S.-L. Wu, Y. Dai, X. Huang, V. Srinivasan and J. W. Weidner, J Electrochem Soc, 164, E3592 (2017).T. R. Garrick, X. Huang, V. Srinivasan and J. W. Weidner, J Electrochem Soc, 164, E3552 (2017).D. J. Pereira, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 166, A1251 (2019).D. J. Pereira, M. A. Fernandez, K. C. Streng, X. X. Hou, X. Gao, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 167, 080515 (2020).T. R. Garrick, J. Gao, X. Yang and B. Koch, J. Electrochem. Soc. (2021).D. J. Pereira, A. M. Aleman, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 169, 020577 (2022).M. Verbrugge, D. Baker and X. Xiao, J Electrochem Soc, 163, A262 (2016).M. Verbrugge, D. Baker, B. Koch, X. Xiao and W. Gu, J Electrochem Soc, 164, E3243 (2017).D. R. Baker and M. W. Verbrugge, J Electrochem Soc, 165, A3952 (2018).D. R. Baker and M. W. Verbrugge, J Electrochem Soc, 167, 013504 (2019).D. R. Baker, M. W. Verbrugge and W. Gu, J Electrochem Soc, 166, A521 (2019).M. W. Verbrugge, X. Xiao and D. R. Baker, J Electrochem Soc, 167, 080523 (2020).

Thermodynamic Analysis of Coal Derived Graphite for Battery Anodes Using the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost. As the time from initial design to manufacture of electric vehicles is decrease, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, models that have a basis in physics, rather than purely empirical representations, are necessary to allow engineers to drive design through a linkage to manufacturing methods. In this study, we apply the Multi-Species, Multi-Reaction model as popularized by Verbrugge and Baker to an electrochemical system comprised of a counter electrode and a working electrode synthesized from graphite derived from coal.To do this, the open circuit voltage of the coal derived graphite and a standard commercially available graphite was quantified. Linear sweep voltammetry provided insight into the shift in electrochemical reactions based on the structure and composition of the coal derived graphite. This then allows the MSMR model to capture the thermodynamic performance of the coal derived graphite, and sheds further insight into the performance compared to the standard commercially available system. Commentary on the thermodynamic differences between the systems will be provided and additional analytical techniques may be used to rationalize differences in performance.

Neodymium Metal Production Via Chloride Based Molten-Salt Electrolysis

The extraction and purification of metals such as aluminum has relied on the electrowinning process for decades. The Hall-Héroult process, developed in 1885, utilizes a molten salt electrolyte to electrochemically produce aluminum metal (Al) and carbon dioxide (CO2).1–3 Similar molten salt techniques exist for a variety of other metals including the rare earth metal Neodymium (Nd). Neodymium has seen significant increases in demand from increased production of wind turbines, electric vehicles, and hard disk drives that use neodymium–iron–boron (Nd–Fe–B) permanent magnets. 4,5 The current procedure for neodymium processing uses a neodymium and lithium fluoride molten salt electrolyte with a sacrificial carbon anode to convert neodymium oxide (Nd2O3) and carbon to neodymium metal and CO2.4,6 As an unfortunate byproduct of the fluoride containing molten salt, perfluorocarbons (PFCs) can also be produced simultaneously. The formation of PFCs combined with the emission of other greenhouse gases (CO,CO2) makes the current process dangerous and undesirable from an environmental standpoint. Due to this, few places currently produce neodymium metal and virtually none is produced in the United States, creating supply chain risks with dire consequences.5 An alternative molten salt process has been proposed where rather than directly converting neodymium oxide to neodymium metal, the oxide is first converted to chloride salt form by reaction with hydrochloric acid. The neodymium salt is then dissolved into a chloride salt based melt and neodymium is electroplated via the below set of reactions.7,8 Cathode: 2NdCl3 + 6e- → 2Nd(solid) + 6Cl- Anode: 6Cl- → 3Cl2 + 6e- Overall: 2NdCl3 → 2Nd(solid) + 3Cl2 This process has several distinct advantages. The chlorine reaction eliminates the need for a sacrificial anode material as well as the production of carbon dioxide. The chloride based molten salt also eliminates the formation of PFCs. The chlorine is then recycled to make more hydrochloric acid for use in converting neodymium oxide to chloride.This talk focuses on recent advances to improve purity and lower energy consumption (kWh/kg). We evaluate anode and cathode behavior during this neodymium chloride molten salt process. Over-potential and stability of various anode materials are investigated in order to minimize energy consumption and ensure long life of process materials. A new stable analytic cathode is demonstrated which is lowers chlorine over-potential by more than 200 mV at current density of 250 mA/cm2.The effect of various plating conditions such as current density and substrate material are investigated to determine impact on deposit quality, coulombic efficiency, and metal purity. Highly porous Nd deposits are known to form in chloride molten salt but are undesirable due to the energy required to separate out the high volume fraction of salt remaining in the solid sponge. Effects of temperature and electrolyte composition on deposit morphology are investigated and improvements toward densifying the sponge to minimize post electrolysis purification are reported. This proof of concept work aims to develop a safe, sustainable and environmentally friendly path towards large scale production of rare earth elements. Reactor design and cathode efficiency results are based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Advanced Manufacturing Office, Award Number DE-EE0009434. Anode design work was supported through the Critical Materials Institute, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Portions of this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. T. R. Beck, Electrochem. Soc. Interface, 23, 36–37 (2014).G. G. Botte, Electrochem. Soc. Interface, 23, 49–55 (2014).W. E. Haupin, J. Chem. Educ., 60, 279–282 (1983).M. F. Chambers and J. E. Murphy, Electrolytic production of neodymium metal from a molten chloride electrolyte.B. Sprecher, R. Kleijn, and G. J. Kramer, Environ. Sci. Technol., 48, 9506–9513 (2014).V. S. Cvetković et al., Met. 2020, Vol. 10, Page 576, 10, 576 (2020).R. Akolkar, J. Electrochem. Soc., 169, 043501 (2022).D. Shen and R. Akolkar, J. Electrochem. Soc., 164, H5292–H5298 (2017).

Multi-Agent Reinforcement Learning for Extended Flexible Job Shop Scheduling

An extended flexible job scheduling problem is presented with characteristics of technology and path flexibility (dual flexibility), varied transportation time, and an uncertain environment. The scheduling can greatly increase efficiency and security in complex scenarios, e.g., distributed vehicle manufacturing, and multiple aircraft maintenance. However, optimizing the scheduling puts forward higher requirements on accuracy, real time, and generalization, while subject to the curse of dimension and usually incomplete information. Various coupling relations among operations, stations, and resources aggravate the problem. To deal with the above challenges, we propose a multi-agent reinforcement learning algorithm where the scheduling environment is modeled as a decentralized partially observable Markov decision process. Each job is regarded as an agent that decides the next triplet, i.e., operation, station, and employed resource. This paper is novel in addressing the flexible job shop scheduling problem with dual flexibility and varied transportation time in consideration and proposing a double Q-value mixing (DQMIX) optimization algorithm under a multi-agent reinforcement learning framework. The experiments of our case study show that the DQMIX algorithm outperforms existing multi-agent reinforcement learning algorithms in terms of solution accuracy, stability, and generalization. In addition, it achieves better solution quality for larger-scale cases than traditional intelligent optimization algorithms.

Modeling, Model Calibration, and Characterization of Graphite Anodes from Coal Derived Carbon for Battery Applications

Most current production electric vehicles (EVs) contain cells with a battery pack or module in order to maintain electrical conductivity, prevent fatigue due to vibrations, and provide efficient cooling. Various module hardware has to be designed in order to facilitate the efficient rejection of heat and contain volume change due to operation and battery cell aging. As we see a shift towards EVs both globally and domestically, the time from concept development to vehicle production needs to rapidly decrease. The use of model-based engineering is critical to driving rapid design and virtual prototyping of electric vehicles to ensure that battery module components meet EV requirements.Currently, empirical data is used to characterize and parameterize battery models that are used to drive design decisions at the battery cell and battery module level. Typical vehicle level use profiles such as the Hybrid Pulse Power Characterization (HPPC) profile, constant rate discharge, constant rate charging, and US06 drive cycles are traditionally used to parameterize battery models. In this work, we discuss select cell level testing profiles, evaluate the electrochemical transport and reaction parameters that are estimated using a porous electrode model, and provide insight and recommendations based on data from coal derived graphite for battery applications.References Garrick, T. R., Gao, J., Yang, X., & Koch, B. J. (2021). “Modeling Electrochemical Transport within a Three-Electrode System.” Journal of The Electrochemical Society, 168(1), 010530. Lopata, J. S., Garrick, T. R., Wang, F., Zhang, H., Zeng, Y., & Shimpalee, S. (2023). “Dynamic Multi-Dimensional Numerical Transport Study of Lithium-Ion Battery Active Material Microstructures for Automotive Applications.” Journal of The Electrochemical Society, 170(2), 020530.

The role of multi-level climate governance in urban transport politics

Throughout the 20th century, the automobile industry developed based on the production of vehicles for private use, powered by fossil fuels. As a result, the transport sector is the one that uses the most energy in Brazil (32.5%) and the second most emitting greenhouse gases (GHG), reaching 13% of total national emissions. The main challenges in the transition to decarbonization in this segment are in Brazilian cities, where 84% of the population lives and whose road mode is predominant in the movement of people and goods. As a measure to adapt and mitigate climate impacts, local governments are investing in new mobility technologies, such as ride-sharing, biofuels and electric and autonomous vehicles. Althought the convergence between technological transition and climate policies is still diffuse and fragmented, requiring integrated and multi-level governance processes. To deepen the understanding of this scenario in the Brazilian context, this article plans to identify the main actors involved in the process of transition to sustainability in the Brazilian urban transportation sector based on a systematic review of the literature applied to the case study of urban passenger mobility in the megacity of São Paulo.

Electrical-hydraulic Modeling and Simulation in MATLAB/Simulink of an Industrial Multi-service Vehicle for Tunneling

The land transport sector has gone through multiple phases of evolution in vehicle design, development, and manufacturing. In particular, the construction sector continues to move towards autonomous vehicles, which have been one of the major trends and have become a hot topic in the industrial and academic world. With this new technology of assistance systems, which control the hydraulic actuators of a car (steering wheel, accelerator, and brake), humans are freed from driving tasks and the number of traffic accidents will be reduced. The modeling and simulation phases play a major role in the development of the construction machine in order to simulate the dynamic behavior of the vehicle and adjust all the parameters beforehand, so that the automated functionality will be easy to realize, and safety will be improved with high accuracy. The objective of this paper is to design a hydro-electric industrial vehicle model for the company METALLIANCE using MATLAB/Simulink environment and compare its simulation with experimental tests. The study addresses the modeling of industrial machines based on the mathematical description of the vehicle dynamics by defining for real-time evaluation of the different vehicle parameters, verifying, and validating the simulation model by comparison with real recorded data.

Using insights on potential users’ behavior and transport requirements to inform the development of a more sustainable vehicle concept as part of a mobility transition

Current mobility systems put a burden on people and the environment, e.g., through greenhouse gas emissions, and depletion of natural resources. Therefore, a mobility transition including changes in legislation, infrastructure, and behavior as well as socio-technical innovations is required. Against this backdrop, the inter- and transdisciplinary project presented in this article aims at developing a new vehicle for individual everyday travel. Target characteristics of the vehicle are: resource-efficient, low in harmful substances in its components, and low on greenhouse gas emissions while driving. To inform the vehicle’s development, n = 730 citizens of a medium-sized university city and its surrounding areas in central Germany took part in a survey on their mobility behavior, intention to switch to the new vehicle, their preferences for possible product features, payment models, and road use. Regression analyses revealed that socioeconomic factors (income, children in the household), individual travel characteristics (travel distance, motorization of vehicle), and psychological factors (innovativeness, weather resistance, travel habit strength, attitudes towards cars and bicycles) explained significant portions of the observed variance in participants’ intention to switch from current travel modes to the new vehicle. Furthermore, our results suggest that the new vehicle may be particularly attractive to potential users if it combines advantageous characteristics of bicycles and cars. Compared to sustainability-relevant aspects of vehicle usage, participants ascribed less importance to aspects of vehicle production and disposal. These learnings provide valuable insights for actors in industry, politics, design, and research striving to promote socio-technical innovations for a transition towards more sustainable mobility.

Design automation system synchronization for cyber physical system with dynamic voltage and frequency scaling in industry 5.0

Recent innovations in determining power—including the Internet of Things, M2M, online services, computational AI, and ARM-based big little multicores for encased applications—have aided in developing industrial process automation. Advanced IP-enabled, the fifth edition of Industry guidelines, are being implemented via actuators, sensing devices, and processors in machinery automation. This allows for increased degrees of competence with less human participation. Because of these novel innovations, the SCPS (Smart et al.) will be pivotal in the next industrialization phase. Multiple integrated systems with varying software are interconnected in an SCPS to perform tasks such as calculation, interaction, supervision, and action. Based on our findings, we propose an inconsistent structure for SCPS that facilitates the execution of composite workflow dynamics via electrical, pneumatic, and hydrodynamic operations. By modeling system problems, instrument postponement, operator interruption, and translation interruption, the proposed design allows for the separation of all components of an operational change, including calculation, oversight, interactions, and activation. This allows us to disentangle these many components. Voltage frequency islands (VFI) with an elevated level of flexibility are used to allocate intellectually integrated components to the many different physical operations, with the amount of flexibility varying from procedure to procedure. All modeled process parameters are fine-tuned using the Variable Volt and Fundamental Shifting methods. In the coming era of manufacturing 5.0, where human involvement is also a part of the procedure in different industries like fuel, compost, paper goods, concrete, space travel, and motor vehicle manufacturing, the suggested layout would be best suited for implementation.

Overestimated environmental benefits of short-term changes in mobility behaviour: The case of Berlin during COVID-19

The COVID-19 pandemic changed urban mobility patterns in unprecedented ways with movement decreasing, few public transport customers, and empty streets turning into pop-up bike lanes. Accordingly, a decrease in local air pollution was reported at the start of the pandemic and models suggested a lower carbon footprint of urban mobility. Here, we offer a critical discussion of the indirect environmental impacts that can be inferred from short-lived mobility behaviour. Examining Berlin, we analyse to what extent transport volume and modal split influenced direct and indirect greenhouse gas emissions throughout the pandemic (2020–2022). The analysis combines traffic counts and survey data with process-specific life cycle assessment factors. The results show that reductions in the carbon footprint of mobility during the pandemic stem largely from a short-term decline in car use, while the modal split became more carbon intensive. Emission reductions from lower use of public transport were not realised, nor a reduction of indirect emissions from vehicle production due to slowly responding upstream demand and public transport planning. This highlights the need to revise the current assumption of perfectly responding markets in environmental footprint assessment of short-term behavioural change during crises, urban experimentation, and transitions.

Fracture morphology and strength characteristics of poly-lactic acid and poly-ethylene terephthalate glycol composites combined with taguchi method and response surface methodology

The emergence of additive manufacturing has enabled scientists to efficiently construct complex geometries, facilitating the development of novel, high-impact energy-absorbing structures suitable for a wide range of industrial applications. The present study conducted flexural and impact test to quantitatively assess the energy absorption capabilities of polymer composites fabricated through fused filament fabrication. Specifically, the polymer composites investigated were multi-walled carbon nanotubes reinforced poly-lactic acid, carbon fibre reinforced poly-ethylene terephthalate glycol, and carbon fibre reinforced poly-lactic acid. The investigation also examined the influence of different infill patterns and nozzle hole diameters on the polymer composites. The investigation depicts that by altering the process parameters, the flexural strength is improved from 21.079 MPa to 70.653 MPa by 235.18%. The experimental study of impact specimens utilising the Izod impact test demonstrates that the rectilinear infill pattern and a nozzle hole diameter of 0.6 mm result in the highest energy absorption of 37.76 kJ/m2 for carbon fibre reinforced poly-lactic acid. The study revealed that the energy absorption of the specimens was significantly influenced by both the independent and interaction effects of process variables. The application of the fused filament fabrication demonstrates an improved energy absorption, making it suitable for manufacturing of vehicle and aircraft components.

Retrofitting of an Existing Garbage Tipper Truck with an Electric Powertrain and its Renewable Charging Station Concept Based on On-Grid Solar Charging

To tackle the pollution problem the best way is to switch to electric vehicles but when we look at the statistical figures of India’s electric vehicle market we can observe the truth that the electric 2 and 3-wheeler market is good in India but the electric 4-wheeler market is not very good. Policymakers' worries about the growing importance of the Climate Change issue have contributed to India's rising levels of air pollution. There are a lot of gasoline and diesel automobiles on the road that is to blame for the severe pollution. 25 of the 100 most polluted cities in the world, or 14 of the list, are in India, according to a search for the 100 most polluted cities worldwide. Petrol and diesel vehicles continue to run in large numbers in India, causing extremely high pollution. The most harmful pollutants emitted into the environment are PM 2.5, SO2, CO, NOx, and PM 10, and they are also the primary pollutants. Since there are so many vehicles on the highways in Indian cities, we know that the cities are crowded. In such a situation, numerous electric vehicle manufacturers are traveling the nation to display their electric automobiles. Additionally, in India, if an electric vehicle's motor output is less than 250W, neither registration nor a driver's license is necessary to operate one of these vehicles. The category for EVs over 500W is the same as that for gasoline and diesel vehicles. The government will electrify all two-wheelers by the years 2024–2025, and all four-wheelers will be electrified by the years 2030–2040. The difficulty now is that many OEMs, auto-ancillaries, and automobile manufacturers intend to enter the market for electric cars in response to these encouraging moves. And when we discuss any vehicle, the mileage or the distance traveled is a key issue. Additionally, electric vehicles, such as 4-wheelers, will compete with conventional cars powered by internal combustion engines, which today give excellent mileage. However, reducing pollution is a crucial issue, and I think electric automobiles can do it more effectively. The transformation of an existing diesel tipper truck into an electric and on-grid-based solar renewable charger is described in this research. This paper discusses the creation and evaluation of various car parts and accessories. This outlines how to go from a mechanical drivetrain to an electric drivetrain. And the charger works on the on-grid solar-based renewable charger.

Investigating Investment Plans for Expanding Battery and Electric Vehicle Production in Europe

There has been significant EV sales growth in Europe, benefiting from its policies for promoting electric vehicles (EVs) and investments in manufacturing. This study investigates the investment announcements for EV and battery production announced by manufacturers and compares them to four scenarios with different EV penetration levels in Europe. This study projects the required capacities and estimates the investment needs to meet different EV sale targets in each scenario. The investigations show that, for Europe to achieve 60% new EV sales by 2030 and to be on track for 100% by 2035, its 4.8 million planned production capacity of EVs would fall short of the needed 9.2 million in 2030. The gap could close to 2.0 million when tentative announcements are counted. The results for batteries indicate that tentative plans are adequate and firm plans can satisfy most scenarios by 2030. More investments into EV production, along with policy support and incentives, are needed for more rapid scenarios.

AN EVALUATION OF SOLID-STATE LIDAR FOR LOCALIZATION AND HD POINT CLOUD MAPPING

Abstract. Cost-effective navigation and positioning systems for autonomous vehicles has become a key focus of research in recent years. Having an accurate position within a lane is vital to enabling high levels of automation and improving safety. Traditionally, vehicle navigation and positioning systems have relied heavily on the Global Navigation Satellite System (GNSS), particularly in open-sky scenarios. However, GNSS signals can be easily disrupted by environmental interferences. These include phenomena such as urban canyons, which result from multi-path interferences, as well as challenges posed by Non-Line-of-Sight (NLOS) situations. In the pursuit of developing robust systems resilient to such issues, the concept of sensor fusion has been widely employed. Among all sensors used in commercial self-driving vehicles, mechanical LiDAR is the primary sensor. Utilizing point cloud data from LiDAR and registering it with a prior point cloud map can result in highly accurate position results. However, the high cost of mechanical LiDAR has limited the mass production of point cloud map and autonomous vehicle. In this paper, we evaluate several successful Simultaneous Localization and Mapping (SLAM) architectures from LiDAR-based to LiDAR-Inertial-based using single Solid-State LiDAR (SSL). Last, we proposed a single SSL mapping and localization framework that can achieve 36 centimeters 3D RMSE and 0.5 degree accuracy in heading estimation.

The Impact of Chinese New Energy Vehicle Companies' Corporate Social Responsibility Actions on Stakeholders - Taking SAIC as an Example

Corporate social responsibility is also an important strategy for the development of today's businesses. The automotive industry has always been a rapidly growing sector. With the increasing awareness of environmental protection, the automotive industry is innovating and developing new energy vehicles for production and sale. This article analyzes the impact of corporate social responsibility of Chinese new energy vehicle companies on stakeholders by reading a large number of scholarly literature and combining it with the case of SAIC Motor Corporation Limited. The analysis reveals that the company still lacks self-sufficiency in core technologies, so SAIC Motor Corporation should increase its investment in research and development. The contribution of the company's infrastructure construction is insufficient; hence it is recommended that SAIC Motor Corporation should improve the construction of infrastructure for new energy vehicles. The company lacks a more innovative product strategy; therefore it is suggested that SAIC Motor Corporation should increase its investment in innovative strategies.

Applying the Operational Design Domain Concept to Vehicles Equipped with Advanced Driver Assistance Systems for Enhanced Safety

Advanced driver assistance systems (ADASs) assist drivers by alerting them of the occurrence of events based on the sensing capabilities of the vehicle, reducing the effort required by drivers. Most vehicles that are recently launched vehicles have been endowed with ADAS, thereby significantly reducing traffic accidents. However, the Insurance Institute for Highway Safety has reported that traffic accidents caused by driver negligence may increase as drivers have become accustomed to using ADAS. Therefore, drivers must be provided with sufficient information on the appropriate use of ADAS through user manuals. In this study, the regulations regarding the presentation of the operational design domain (ODD) in ADAS user manuals were analyzed. The results indicated that most user manuals do not sufficiently specify the ODD, which is claimed important by various organizations for ensuring safe driving. Additionally, the expression of the limitations and performance of ADAS is ambiguous because most countries are not regulated to explicitly present the ODD when writing ADAS user manuals. Therefore, in this study, the ODD guidelines for presenting ADAS specific to vehicle manufacturers and governments have been outlined in addition to guidelines for drivers on using ADAS. These guidelines can contribute to the development of clear ADAS user manuals, which in turn can ensure the safe driving of ADAS-equipped vehicles.

Sharing mode selection and optimal pricing for an electric vehicle manufacturer

This paper studies the sharing mode selection and optimal pricing for an electric vehicle manufacturer (EVM). We evaluate three sharing modes, i.e. Mode N, car sales business only, Mode S, car sales business and car-sharing service provided by a self-built sharing platform, and Mode T, car sales business and car-sharing service provided by a third-party sharing platform. Further, we consider two types of government subsidy policies: purchase and production subsidies. We find that for purchase subsidies, the EVM should select Mode S if the transaction cost per sharing service is low, and select Mode T otherwise; for production subsidies, the EVM should select Mode S. Regardless of the subsidy policy, the optimal sales prices of EVs under Mode N and Mode S are the same, but both are lower than that under Mode T. The optimal rental price of EVs under Mode S is lower than that under Mode T.

Enabling battery circularity: Unlocking circular business model archetypes and collaboration forms in the electric vehicle battery ecosystem

Achieving battery circularity is crucial for meeting the targets of net-zero emission vehicles by 2030 and enabling climate-neutral transportation by 2050. To facilitate this transition, firms operating in the electric vehicle (EV) battery ecosystem must reassess their value creation, capture, and delivery methods. Although EV battery second life presents a promising solution for circularity, many vehicle manufacturers and stakeholders in the battery ecosystem struggle to adapt their organizations internally and externally due to a lack of insights into suitable circular business models. The purpose of this study is to identify viable archetypes of circular business models for EV battery second life and examine their implications on company collaborations within the EV battery ecosystem. Three main archetypes of circular business models are identified (i.e., extending, sharing, and looping business models) and further divided into eight sub-archetypes. These models are elucidated in terms of key business model dimensions, including value proposition, value co-creation, value delivery, and value capture. The paper provides visual representations of the necessary interactions and collaborations among companies in the EV battery ecosystem to effectively implement the proposed business model archetypes. This research contributes to the theory of circular business models in general, with specific relevance to EV battery circularity.

Smooth sailing ahead? Policy options for China's new energy vehicle industry in the post-subsidy era

The Chinese government views the development of new energy vehicles (NEVs) as a key measure to achieve sustainable development. In 2020, the government proposed the development goals of achieving carbon peak in the automotive industry around 2028 and ensuring NEV sales account for over 50 % by 2035 (referred to as the “two objectives”). Against the backdrop of the cancellation of NEV purchase subsidies in 2023, it is crucial to investigate the direction and intensity of various industry policies' effects and actively adjust industrial policies to achieve the “two objectives”. From the perspective of the Multi-level Perspective (MLP), the technological transition in the automotive industry is a process of legitimacy transfer between new and old technologies driven by the interaction of socio-technical landscape, socio-technical regime, and niches at three levels. This paper, based on the MLP, constructs a system dynamics (SD) model that includes four loops: research and development (R&D), production, sales, and legitimacy competition. Using the SD model, we analyze the direction and intensity of existing policies, in addition to five potential policies, to achieve the objectives. Our findings indicate that without policy adjustments, China's current measures will not meet the “two objectives” in a timely manner. Prioritizing battery recycling, curtailing fuel vehicle (FV) production, facilitating scrapping of FVs and enacting carbon trading policies are pivotal for progress, contrasting with the modest impact of R&D subsidies. A coordinated policy strategy coupled with expedited carbon trading initiatives is essential for the NEV sector's post-subsidy transition to meet the objectives.

A Novel Efficient Dual-Gate Mixed Dilated Convolution Network for Multi-Scale Pedestrian Detection

With the increasing use of onboard high-speed computing systems, vehicle manufacturers are offering significant advanced features of driver assistance systems. Pedestrian detection is one of the major requirements of such systems, which commonly use cameras, radar, and ultrasonic sensors. Image recognition based on captured image streams is one of the powerful tools used for the detection of pedestrians, which exhibits similarities and distinguishing features compared to general object detection. Although pedestrian detection has advanced significantly along with deep learning, some issues still need to be addressed. Pedestrian detection is essential for several real-world applications and is an initial step in outdoor scene analysis. Typically, in a crowded situation, conventional detectors are unable to distinguish persons from each other successfully. This study presents a novel technique, based on the Dual Gate Mixed Dilated Convolution Network, to address this problem by adaptively filtering spatial areas where the patterns are still complicated and require further processing. The proposed technique manages obscured patterns while offering improved multiscale pedestrian recognition accuracy.