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The initial cost of battery electric vehicles (BEVs) is higher than internal combustion engine-powered vehicles (ICEVs) due to expensive batteries. Various factors affect the total cost of ownership of a vehicle. In India, consumers are concerned with a vehicle’s initial purchase cost and prefer owning an economical vehicle. The higher cost and shorter range of BEVs compared to ICEVs severely limit their penetration in the Indian market. However, government subsidies and incentives support BEVs. The total cost of ownership assessment is used to evaluate the entire cost of a vehicle to find the most economical option among different powertrains. This study compares 2W (two-wheeler) and 4W (four-wheeler) BEV’s cost vis-à-vis equivalent ICEVs in Delhi and Mumbai. The cost analysis assesses the current and future government policies to promote BEVs. Two assumed policies were applied to estimate future scenarios.

Abstract This article presents a technical study on the integration of hybrid renewable energy sources (RES) with vehicle-to-grid (V2G) technology, aiming to enhance energy efficiency, grid stability, and mitigating power imbalances. The growing adoption of RES and electric vehicles (EV) necessitates innovative solutions to mitigate intermittency and optimize resource utilization. The study’s primary objective is to design and analyze a hybrid distribution generation system encompassing solar photovoltaic (PV) and wind power stations, along with a conventional diesel generator, connected to the utility grid. A V2G system is strategically embedded within the microgrid to facilitate bidirectional power exchange between EV and the grid. Methodologically, MATLAB/Simulink® 2021a is employed to simulate the system’s performance over one day.

Abstract A multiple output dynamically adjustable capacity system (MODACS) is developed to provide multiple voltage output levels while supporting varying power loads by switching multiple battery strings between serial and parallel connections. Each module of the system can service either a low voltage bus by placing its strings in parallel or a high voltage bus with its strings in series. Since MODACS contains several such modules, it can produce multiple voltages simultaneously. By switching which strings and modules service the different output rails and by varying the connection strategy over time, the system can balance the states of charge (SOC) of the strings and modules. A model predictive control (MPC) algorithm is formulated to accomplish this balancing. MODACS operates in various power modes, each of which imposes unique constraints on switching between configurations.

Abstract Battery electric vehicles (EVs) bring significant benefits in reducing the carbon footprint of fossil fuels and new opportunities for adopting renewable energy. Because of their high-energy density and long cycle life, lithium-ion batteries (LIBs) are dominating the battery market, and the consumer demand for LIB-powered EVs is expected to continue to boom in the next decade. However, the chemistry used in LIBs is still vulnerable to experiencing thermal runaway, especially in harsh working conditions. Furthermore, as LIB technology moves to larger scales of power and energy, the safety issues turn out to be the most intolerable pain point of its application in EVs. Its failure could result in the release of toxic gases, fire, and even explosions, causing catastrophic damage to life and property. Vehicle fires are an often-overlooked part of the fire problem. Fire protection and EV safety fall into different disciplines.

Abstract This article investigates the performance of a low-cost throttle-by-wire-system (TbWS) for two-wheeler applications. Mopeds/scooters are still restricted as environmentally harmful. TbWSs can contribute to environmental protection by replacing conventional restrictors. Its consisting of an anisotropic magnetoresistance (AMR) throttle position sensor and a position-controlled stepper motor-driven throttle valve actuator. The decentralized throttle position sensor is operating contactless and acquires redundant data. Throttle valve actuation is realized through a position-controlled stepper motor, sensing its position feedback by Hall effect. Using a PI controller, the stepper motor position is precisely set. Both units transmit and receive data by a CAN bus. Furthermore, fail-safe functions, plausibility checks, calibration algorithms, and energy-saving modes have been implemented.

Abstract In autonomous technology, uncrewed aircraft systems have already become the preferred platform for the research and development of flight control systems. Although they are subjected to following and satisfying complicated scenarios of control stations, this high dependency on a specific control framework limits them in their application process and reduces the flight self-organizing network. In this article, we present a developed multilayer control system protocol with the additional supportive manned aircraft layer (Tender). The novelty of the introduced model is that uncrewed aircraft systems are monitored and navigated by the tender, and then based on the suggested scheme, data flows are controlled and transferred across the network by the developed cloud–robotics approach in the ground station layer.

Abstract Heavy-duty on-road engines are expected to conform to an ultralow NOx (ULNOx) standard of 0.027 g/kWh over the composite US heavy-duty transient federal test procedure (HD-FTP) cycle by 2031, a 90% reduction compared to 2010 emissions standards. Additionally, these engines are expected to conform to Phase 2 greenhouse gas regulations, which require tailpipe CO2 emissions under 579 g/kWh. This study experimentally demonstrates the ability of high fuel stratification gasoline compression ignition (HFS-GCI) to satisfy these emissions standards. Steady-state and transient tests are conducted on a prototype multi-cylinder heavy-duty GCI engine based on a 2010-compliant Cummins ISX15 diesel engine with a urea-SCR aftertreatment system (ATS). Steady-state calibration exercises are undertaken to develop highly fuel-efficient GCI calibration maps at both cold-start and warmed up conditions.

Abstract The emerging use of rechargeable batteries in electric and hybrid electric vehicles and distributed energy systems, and accidental fires involving batteries, has heightened the need for a methodology to determine the root cause of the fire. When a fire involving batteries takes place, investigators and engineers need to ascertain the role of batteries in that fire. Just as with fire in general, investigators need a framework for determining the role that is systematic, reliant on collection and careful analysis of forensic evidence, and based on the scientific method of inquiry. This article presents a systematic scientific process to analyze batteries that have been involved in a fire. It involves examining Li-ion cells of varying construction, using a systematic process that includes visual inspection, x-ray, CT scan, and possibly elemental analysis and testing of exemplars.

Abstract TOC

Abstract Due to the presence of uncertain disturbances in the actual steering system, disturbances in the system may affect the handling stability of the vehicle. Therefore, this article proposes an integrated steering system control strategy with stronger anti-disturbance performance. When disturbances exist in the system, the proposed control strategy effectively reduces the attitude changes during the vehicle steering process. In the upper-level control strategy, a variable transmission ratio curve is designed to coordinate the high-speed handling stability and low-speed steering sensitivity of the vehicle. On this basis, a sideslip angle observer is proposed based on the extended state observation theory, which does not depend on an accurate system model, thus determining the intervention timing of the active front wheel steering system. In the lower-level control strategy, DR-PI/DR-PID controllers are designed for the integrated steering system.

Abstract A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration proportional–integral–derivative (PID) control. A two-degrees-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined, and the Routh stability criterion method was introduced to assess the impact of PID control on vehicle stability. The PID control parameters are tuned using the differential evolution algorithm, and to improve the algorithm’s adaptive ability, an adaptive operator is introduced, so that the mutation factor of differential evolution algorithm can change with the number of iterations.

Abstract Lithium-ion (LI) batteries are widely used to power electric vehicles (EVs), owing to their high charge density, to minimize the environmental pollution caused by fossil fuel-based engines. It experiences an enormous amount of heat generation during charging and discharging cycles, which results in higher operating temperatures and thermal nonuniformity. This affects performance, useful battery life, and operating costs. This can be mitigated by an effective battery thermal management system (BTMS) to dissipate the heat there by safeguarding the battery from adverse thermal effects and ensuring high performance, safety, and longevity of the battery.

Abstract An automatic collision avoidance control method integrating optimal four-wheel steering (4WS) and direct yaw-moment control (DYC) for autonomous vehicles on curved road is proposed in this study. Optimal four-wheel steering is used to track a predetermined trajectory, and DYC is adopted for vehicle stability. Two single lane change collision avoidance scenarios, i.e., a stationary obstacle in front and a moving obstacle at a lower speed in the same lane, are constructed to verify the proposed control method. The main contributions of this article include (1) a quintic polynomial lane change trajectory for collision avoidance on curved road is proposed and (2) four different kinds of control method for autonomous collision avoidance, namely 2WS, 2WS+DYC, 4WS, and 4WS+DYC, are compared. In the design of DYC controller, two different feedback control methods are adopted for comparison, i.e., sideslip angle feedback and yaw rate feedback.

Abstract The global automotive industry’s shift toward electrification hinges on battery electric vehicles (BEV) having a reduced total cost of ownership compared to traditional vehicles. Although BEVs exhibit lower operational costs than internal combustion engine (ICE) vehicles, their initial acquisition expense is higher due to expensive battery packs. This study evaluates total ownership costs for four vehicle types: traditional ICE-based car, BEV, split-power hybrid, and plug-in hybrid. Unlike previous analyses comparing production vehicles, this study employs a hypothetical sedan with different powertrains for a more equitable assessment. The study uses a drive-cycle model grounded in fundamental vehicle dynamics to determine the fuel and electricity consumption for each vehicle in highway and urban conditions. These figures serve a Monte Carlo simulation, projecting a vehicle’s operating cost over a decade based on average daily distance and highway driving percentage.

Abstract In order to enhance the path-tracking accuracy and adaptability of the electric flatbed vehicle (EFV) in the soft-target vehicle test system, an improved controller is designed based on the linear quadratic regulator (LQR) algorithm. First, the LQR feedback controller is designed based on the EFV dynamics tracking error model, and the genetic algorithm is utilized to obtain the optimal weight coefficient matrix for different speeds. Second, a weight coefficient matrix compensation strategy is proposed to address the changes in the relationship between the vehicle–road position and attitude caused by external disturbances and the state of EFV. An offline parameter table is created to reduce the computational load on the microcontroller of EFV and enhance real-time path-tracking performance. Furthermore, an adaptive preview time control strategy is added to reduce the overshooting caused by control delay. This strategy is based on road curvature and traveling speed.

Abstract This study underscores the benefits of refining the intralogistics process for small- to medium-sized manufacturing businesses (SMEs) in the engineer-to-order (ETO) sector, which relies heavily on manual tasks. Based on industrial visits and primary data from six SMEs, a new intralogistics concept and process was formulated. This approach enhances the value-added time of manufacturing workers while also facilitating complete digital integration as well as improving transparency and traceability. A practical application of this method in a company lead to cutting its lead time by roughly 11.3%. Additionally, improved oversight pinpointed excess inventory, resulting in advantages such as reduced capital needs and storage requirements. Anticipated future enhancements include better efficiency from more experienced warehouse staff and streamlined picking methods. Further, digital advancements hold promise for cost reductions in administrative and supportive roles.

Abstract Being an engineer-to-order (ETO) operating industry, the control cabinet industry faces difficulties in process and workplace optimizations due to changing requirements and lot size one combined with volatile orders. To optimize workplaces for employees, current literature is focusing on ergonomic designs, providing frameworks to analyze workplaces, leaving out the optimal design for productivity. This work thus utilizes a Kano analysis, collecting empirical data to identify essential design requirements for assembly workplaces, incorporating input from switchgear manufacturing employees. The results emphasize the need for a balance between ergonomics and efficiency in workplace design. Surprisingly, few participants agree on the correlation between improved processes and workspaces having a positive impact on their well-being and product quality.

Abstract Accurate estimation of traction force is essential for the development of advanced control systems, particularly in the domain of autonomous driving. This study presents an innovative approach to enhance the estimation of tire–road interaction forces under combined slip conditions, employing a combination of empirical models and neural networks. Initially, the well-known Pacejka formula, or magic formula, was adopted to estimate tire–road interaction forces under pure longitudinal slip conditions. However, it was observed that this formula yielded unsatisfactory results under non-pure slip conditions, such as during curves. To address this challenge, a neural network architecture was developed to predict the estimation error associated with the Pacejka formula. Two distinct neural networks were developed. The first neural network employed, as inputs, both longitudinal slip ratios of the driving wheels and the slip angles of the driving wheels.

Abstract The swift progress of electric vehicles (EVs) and hybrid electric vehicles (HEVs) has driven advancements in battery management systems (BMS). However, optimizing the algorithms that drive these systems remains a challenge. Recent breakthroughs in data science, particularly in deep learning networks, have introduced the long–short-term memory (LSTM) network as a solution for sequence problems. While graphics processing units (GPUs) and application-specific integrated circuits (ASICs) have been used to improve performance in AI-based applications, field-programmable gate arrays (FPGAs) have gained popularity due to their low power consumption and high-speed acceleration, making them ideal for artificial intelligence (AI) implementation. One of the critical components of EVs and HEVs is the BMS, which performs operations to optimize the use of energy stored in lithium-ion batteries (LiBs).

Abstract One of the key problems of battery electric vehicles is the risk of severe range reduction in winter conditions. Technologies such as heat pump systems can help to mitigate such effects, but finding adequate heat sources for the heat pump sometimes can be a problem, too. In cold ambient conditions below −10°C and for a cold-soaked vehicle this can become a limiting factor. Storing waste heat or excess cold when it is generated and releasing it to the vehicle thermal management system later can reduce peak thermal requirements to more manageable average levels. In related architectures it is not always necessary to replace existing electric heaters or conventional air-conditioning systems. Sometimes it is more efficient to keep them and support them, instead. Accordingly, we show, how latent heat storage can be used to increase the efficiency of existing, well-established heating and cooling technologies without replacing them.