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Abstract This article presents the design and the analysis of a control logic capable of optimizing vehicle’s energy consumption during a braking maneuver. The idea arose with the purpose of enhancing regeneration and health management in electric vehicles with electro-actuated brakes. Regenerative braking improves energy efficiency and allows a considerable reduction in secondary emissions, but its efficiency is strongly dependent on the state of charge (SoC) of the battery. In the analyzed case, a vehicle equipped with four in-wheel motors (one for each wheel), four electro-actuated brakes, and a battery was considered. The proposed control system can manage and optimize electrical and energy exchanges between the driveline’s components according to the working conditions, monitoring parameters such as SoC of the battery, brake temperature, battery temperature, motor temperature, and acts to optimize the total energy consumption.

Abstract Measurements of air–fuel ratio (AFR) and λ (AFRactual/AFRstoich) are crucial for understanding internal combustion engine (ICE) performance. However, current λ sensors suffer from long light-off times (on the order of seconds following a cold start) and limited time resolution. In this study, a four-color mid-infrared laser absorption spectroscopy (LAS) sensor was developed to provide 5 kHz measurements of temperature, CO, CO2, and NO in engine-out exhaust. This LAS sensor was then combined with 1 kHz hydrocarbon (HC) measurements from a flame ionization detector (FID), and the Spindt exhaust gas analysis method to provide 1 kHz measurements of λ. To the authors’ knowledge, this is the first time-resolved measurement of λ during engine cold starts using the full Spindt method. Three tests with various engine AFR calibrations were conducted and analyzed: (1) 10% lean, (2) stoichiometric, and (3) 10% rich.

Abstract This article focuses on the development of an active braking control system tailored for electric vehicles. The essence of this system lies in its ability to regulate the slip coefficient to optimize traction during braking, thereby maximizing energy recuperation. In the context of the simulation on enhancing regenerative energy capture in electric vehicles, the use of integral sliding mode control (ISMC) as an alternative for regulating braking performance can be understood through a comparison of two key output variables in braking control systems: wheel deceleration and wheel slip. Traditionally, wheel deceleration has been a controlled variable in braking systems, and it is still utilized in some anti-lock braking systems (ABS). It can be easily measured using a basic wheel encoder. However, the dynamic performance of wheel deceleration control may suffer when there are rapid changes in the road surface.

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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 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 A growing interest in electromechanical brakes (EMB) is discernible in the automotive industry finding its climax in an announcement of EMB series production in late 2022 [1]. The introduction of EMB allows for new design opportunities using distributed software on smart actuators. However, additional efforts are needed to ensure continuously high levels of safety even when established design principles in the brake system are changed. This article discusses different safety concepts that could potentially be put in place in EMB actuators. Therefore, safety goals that need to be satisfied by an actuator are derived. Furthermore, three different degrees of complexity are differentiated, evolving to different required electronic control units (ECU) and architectures. Additionally, also the safety of the actuation unit (AU) is considered to realize a holistic safety concept for the actuator. Finally, a conclusion is drawn comparing the different investigated concepts.

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.

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Abstract Throughout the automobile industry, the electronic brake boost technologies have been widely applied to support the expansion of the using range of the driver assist technologies. The electronic brake booster (EBB) supports to precisely operate the brakes as necessary via building up the brake pressure faster than the vacuum brake booster. Therefore, in this article a novel control strategy for the EBB based on fuzzy logic control (FLC) is developed and studied. The configuration of the EBB is established and the system model including the permanent magnet synchronous motor (PMSM), a two-stage reduction transmission (gears and a ball screw), a servo body, reaction disk, and the hydraulic load are modeled by MATLAB/Simulink. The load-dependent friction has been compensated by using Karnopp friction model. Due to the strong nonlinearity on the EBB components and the load-dependent friction, FLC has been used for the control algorithm.

Abstract In this article, an improved brake cooling simulation method is introduced. By this method, the vehicle parameters, such as weight, height of the center of gravity, wheelbase, and the like can be included to calculate the braking thermal load under different operating conditions. The effect of the brake kinetic energy regeneration (BKER) on the braking thermal load can also be calculated by this method. The calculated braking thermal load is then input to a coupled 3D simulation model to conduct flow and thermal simulation to calculate brake disc temperature. It is demonstrated that by this simulation method, the difference between the brake disc temperatures obtained from simulation and vehicle test can be controlled below 5%.

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 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 Composite ceramic brake discs are made of ceramic material reinforced with carbon fibers and offer exceptional advantages that translate directly into higher vehicle performance. In the case of an electric vehicle, it could increase the range of the vehicle, and in the case of conventional internal combustion engine vehicles, it means lower fuel consumption (and consequently lower CO2 emissions). These discs are typically characterized by complex internal geometries, further complicated by the presence of drilling holes on both friction surfaces. To estimate the aerothermal performance of these discs, and for the thermal management of the vehicle, a reliable model for predicting the air flowing across the disc channels is needed. In this study, a real carbon-ceramic brake disc with drilling holes was investigated in a dedicated test rig simulating the wheel corner flow conditions experimentally using the particle image velocimetry technique and numerically.

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 To address the challenge of directly measuring essential dynamic parameters of vehicles, this article introduces a multi-source information fusion estimation method. Using the intelligent front camera (IFC) sensor to analyze lane line polynomial information and a kinematic model, the vehicle’s lateral velocity and sideslip angle can be determined without extra sensor expenses. After evaluating the strengths and weaknesses of the two aforementioned lateral velocity estimation techniques, a fusion estimation approach for lateral velocity is proposed. This approach extracts the vehicle’s lateral dynamic characteristics to calculate the fusion allocation coefficient. Subsequently, the outcomes from the two lateral velocity estimation techniques are merged, ensuring rapid convergence under steady-state conditions and precise tracking in dynamic scenarios.

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.