Browse Topic: Financial management

Items (1,098)
The electrification of off-highway vehicles presents a complex landscape of challenges, particularly in the realm of cost engineering for motors. These challenges stem from technological complexities, use of specialty materials and processes, economics of scale, and operational factors, each requiring careful consideration to ensure accurate and efficient cost modeling. The lack of standardized cost data for specialty materials poses a significant barrier to accurate cost engineering. Furthermore, the cost of key materials and components, such as electrical steel and permanent magnets, can fluctuate due to supply chain disruptions, material shortages, introducing uncertainty into cost projections. The economies of scale play a crucial role in cost engineering for off-highway electrification. Many off-highway vehicles are produced in lower volumes compared to on-road vehicles, which can result in higher unit costs for electric motors and other. In this paper, we delve into the primary
Chauhan, ShivPadalkar, Bhaskar
Zero emission vehicles are essential for achieving sustainable and clean transportation. Hybrid vehicles such as Fuel Cell Electric Vehicles (FCEVs) use multiple energy sources like batteries and fuel cell stacks to offer extended driving range without emitting greenhouse gases. Optimal performance and extended life of the important components like the high voltage battery and fuel-cell stack go a long way in achieving cost benefits as well as environmental safety. For this, energy management in FCEVs, particularly thermal management, is crucial for maintaining the temperature of these components within their specified range. The fuel cell stack generates a significant amount of waste heat, which needs to be dissipated to maintain optimal performance and prevent degradation, whereas the battery system needs to be operated within an optimal temperature range for its better performance and longevity. Overheating of batteries can lead to reduced efficiency and potential safety hazards
BHOWMICK, SAIKATChuri, Chetana
The transition from ICE to EV faces various challenges and innovations in vehicle maintenance. The automotive industry, followed by EV technology, addresses the unique components and systems of electric powertrains, high voltage, and electronic control systems. Unlike traditional cars, EVs should require specialized tools; high voltage safety protocols are trained as personnel. This paper also described the key difference between ICE and EV maintenance. Also, it explained the various challenges related to limited expertise, battery diagnosis, battery replacement, cost analysis, and charging solutions. To understand the various factors of this study involved the EV service industry as smoother transitions.
Raja, SelvakumarBrainee, Daniel SolomonR. S., NakandhrakumarNandagopal, SasikumarPalani, LoganathanMuthiya, S Jenoris
The China Container Freight Index (CCFI) is an important barometer of the global container shipping market. It is very important for participants in the shipping market to understand its composition. This study takes six representative routes as the research objects and conducts a detailed analysis of the composition of CCFI. The freight rate indices of these routes are decomposed and reconstructed by using the Empirical Mode Decomposition (EMD) algorithm, aiming to clarify the economic significance of each route and the fluctuation law of the reconstructed components. The research results show that the freight rate fluctuations of the west Coast, Southeast Asia and Mediterranean routes exhibit a complex nonlinear interdependence, and the simple linear model cannot fully reflect this relationship. On the contrary, the trend components of the European and Mediterranean routes effectively identify and represent the main trends within the original freight rate index. Global major events
Yin, Sitian
Delamination of transparent armor (TA) is one of the costliest and most frustrating failures facing the tactical vehicle community. When purchased, all TA appears equally pristine and has identical protective abilities, but some parts delaminate after only a few years while other parts last over a decade. Recent high delamination rates have resulted in large costs – a Warstopper study showed that transparent armor accounted for 20% of the maintenance cost for the HMMWV. One major advance in the last few years has been the Army-led development of an ‘Accelerated Life Test’ which consistently causes field relevant delamination in transparent armor parts. We present the development of a method to correlate test results with field life, thus allowing for life prediction and life cycle cost analysis. We demonstrate how the life prediction tool can be used to drive purchasing strategies, field use decisions, and vehicle design.
Merrill, Marriner H.Magner, Matthew J.Key, Christopher T.Humphrey, Barry A.
Long-haul truck drivers are mandated to take off-duty time of 10 h (a.k.a. hoteling) before driving. During the hotel phase, drivers spend time inside their trucks (sleeper cabs) and idle the internal combustion engine for comfort by utilizing the heating, ventilation, air-conditioning (HVAC), and other onboard appliances. For one 10-h period, the average cost is about $40, which can be a lot when considering a million truck drivers idling overnight. SuperTruck II is a 48 V mild-hybrid heavy-duty truck with auxiliary loads powered by an onboard battery pack. An optimal control algorithm is developed to charge the battery pack during the drive phase up to a certain state-of-charge (SOC) level, sufficient to meet the power demands of the auxiliary load during the hotel phase. This article captures the research done to predict energy consumption in a mild-hybrid heavy-duty sleeper truck during hoteling. Physics-based gray box models are developed to estimate the power consumption of an
Khuntia, SatvikHanif, AtharAhmed, QadeerLahti, JohnJorgensen, Iner
This article details the development of a plug-in hybrid electric powertrain system for a wheel loader. The work included both computer modeling and fired engine testing. A methodical approach was utilized, which included identifying system requirements, an architecture study, component sizing, and cost analysis. After the optimal system was designed, the engine and hybrid motor were installed in a powertrain test cell and evaluated over an in-use duty cycle. A bespoke utility factor, relevant for wheel loader operation, was developed to enable realistic fuel economy and emissions weighting between charge depleting and charge sustaining operation. Finally, an exhaust heater was used to ensure rapid warmup of the aftertreatment system. Compared to an internal combustion engine–only baseline, the hybrid powertrain system resulted in a 48% reduction in CO2 and an 84% reduction in NOX emissions when operated over an 8-h shift, with daily recharging.
Bachu, PruthviMichlberger, AlexanderMeruva, PrathikBitsis, Daniel Christopher
Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of drive system properties. Estimating these properties in the early stages of development is challenging due to the depth of modelling required. In addition, defined requirements play a critical role in drive system sizing. This paper presents a tool chain for the synthesis of new electrified drive concepts, with emphasis on requirements definition and modelling. The requirements definition method combines market analysis with a generalized calculation and estimation approach, providing a novel perspective. In addition, we introduce mass and cost modelling capabilities integrated into the tool chain. The mass model achieves high accuracy, with deviations of only 1.6 % at the vehicle level and 6.1 % at the component level. Finally, the paper examines the mass and cost
Sturm, AxelHenze, Roman
Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of system properties. Estimating these properties in the early stages of vehicle development is challenging due to the depth of modelling required. In order to enable a cost prognosis for driving assistance and automated driving functions including software and hardware properties a cost model was developed at the Institute of Automotive Engineering. The methodology and cost model focuses on multiple combined approaches. This includes a bottom-up approach for the hardware. The costs of the software components are integrated into the model with the help of existing literature data and an exponential regression. For a comprehensive view of the total costs, the model is the model is also supplemented by a top-down approach for estimating the costs of other hardware components. The
Sturm, AxelHichri, BassemRohde García, ÁlvaroHenze, Roman
This study presents a comprehensive techno-economic assessment (TEA) of an integrated e-methanol production system building upon previously published foundational research utilizing Aspen Plus modeling for e-methanol production from sugar cane and sugar beet biomass. The established integrated system converts biomass into ethanol through fermentation and synthesizes e-methanol using both captured CO2 and syngas derived from biomass residue gasification. This approach maximizes CO2 and biomass utilization, promoting a circular carbon economy. The TEA quantifies capital expenditures (CAPEX), operational expenditures (OPEX), and levelized costs of Methanol (LCOM), providing a detailed economic analysis of the potential for commercializing e-methanol. A sensitivity analysis evaluates the impact of feedstock prices and Technology Readiness Levels (TRL), identifying key leverage points affecting financial viability. The study aims to explore the potential of utilizing existing agricultural
Fernandes, Renston JakeShakeel, Mohammad RaghibNguyen, DucduyIm, Hong G.Turner, James W.G.
The switch to electrified off-highway vehicles can help reduce reliance on hydraulic components that decrease system efficiency via parasitic losses. The off-highway machine industry is embracing new technologies to optimize operations, specifically regarding electric and hybrid off-highway equipment. The electric off-highway equipment market is poised for growth, with an expected 12.5% compound annual growth rate (CAGR) from 2025-2034, reaching over $17 billion, according to Market Research Future. These off-highway vehicles operate on tough terrain and require unprecedented amounts of power for long duty cycles. Diesel engines have always been the conventional application for this kind of work, but now hybrid and electric vehicles are starting to gain traction thanks to new innovations and more investment. While the implications of replacing traditional combustion engines with hybrid or electric counterparts can be intimidating, learning the challenges and opportunities each option
Liu, Zifan
In addition to providing safety advantages, sound and vibration are being utilized to enhance the driver experience in Battery Electric Vehicles (BEVs). There's growing interest and investment in using both interior and exterior sounds for pedestrian safety, driver awareness, and unique brand recognition. Several automakers are also using audio to simulate virtual gear shifting of automatic and manual transmissions in BEVs. According to several automotive industry articles and market research, the audio enhancements alone, without the vibration that drivers are accustomed to when operating combustion engine vehicles, are not sufficient to meet the engagement, excitement, and emotion that driving enthusiasts expect. In this paper, we introduce the use of new automotive, high-force, compact, light-weight circular force generators for providing the vibration element that is lacking in BEVs. The technology was developed originally for vibration reduction/control in aerospace applications
Norris, Mark A.Orzechowski, JeffreySanderson, BradSwanson, DouglasVantimmeren, Andrew
Fuel cell vehicles (FCVs) offer a promising solution for achieving environmentally friendly transportation and improving fuel economy. The energy management strategy (EMS), as a critical technology for FCVs, faces significant challenges of achieving a balanced coordination among the fuel economy, power battery life, and durability of fuel cell across diverse environments. To address these challenges, a learning-based EMS for fuel cell city buses considering power source degradation is proposed. First, a fuel cell degradation model and a power battery aging model from the literature are presented. Then, based on the deep Q-network (DQN), four factors are incorporated into the reward function, including comprehensive hydrogen consumption, fuel cell performance degradation, power battery life degradation, and battery state of charge deviation. The simulation results show that compared to the dynamic programming–based EMS (DP-EMS), the proposed EMS improves the fuel cell durability while
Song, DafengYan, JinxingZeng, XiaohuaZhang, Yunhe
In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals
Miller, BrandonSun, RuixiaoSujan, Vivek
Vehicle sideslip is a valuable measurement for ground vehicles in both passenger vehicle and racing contexts. At relevant speeds, the total vehicle sideslip, beta, can help drivers and engineers know how close to the limits of yaw stability a vehicle is during the driving maneuver. For production vehicles or racing contexts, this measurement can trigger Electronic Stability Control (ESC). For racing contexts, the method can be used for driver training to compare driver techniques and vehicle cornering performance. In a fleet context with Connected and Autonomous Vehicles (CAVS) any vehicle telemetry reporting large vehicle sideslip can indicate an emergency scenario. Traditionally, sideslip estimation methods involve expensive and complex sensors, often including precise inertial measurement units (IMUs) and dead reckoning, plus complicated sensor fusion techniques. Standard GPS measurements can provide Course Over Ground (COG) with quite high accuracy and, surprisingly, the most
Hannah, AndrewCompere, Marc
Automotive industry is growing rapidly with innovations leading to increase in new features and improving the Quality of vehicles. These new components are developed with the available design standards across global OEMs. This Quality research paper aims to address the need of revision of design standards due to environmental factors prevailing in India. With the increase towards autonomous mobility, the number of electronics is also increasing, and this involves hardware & software evaluation. The hardware testing is a point of concern due to increase in the failure rate from the markets. Environment changes are very much evident with the growing economies and OEMs are developing the components with innovation, but if the basic design standards are not revised in parallel with the changing environment, the issues will continue to trouble the end customers. The failed cases data received from across the country was analyzed and observed that the cases are majorly reported from urban
Marwah, RamnikPyasi, PraveenBindra, RiteshGarg, Vipin
In numerous automotive and industrial applications, efficient heat extraction is crucial to prevent system inefficiencies or catastrophic failures. The design of heat exchangers is inherently complex, involving multiple stages defined by the depth of analysis, number of design variables, and the accuracy of physical models. Designers must navigate the trade-offs between highly accurate yet computationally expensive models and less accurate but computationally cheaper alternatives. Multi-fidelity modeling offers a solution by integrating different fidelity models to deliver precise results at a reduced computational cost. In addition to managing these trade-offs, designers often face multi-objective challenges, where optimizing one aspect may lead to compromises in others. Multi-objective optimization, therefore, becomes essential in balancing these competing objectives to achieve the best overall design. In this context, Gaussian Process-based methods have gained prominence as
Chaudhari, PrathameshTovar, Andres
This study evaluates the performance of alternative powertrains for Class 8 heavy-duty trucks under various real-world driving conditions, cargo loads, and operating ranges. Energy consumption, greenhouse gas emissions, and the Levelized Cost of Driving (LCOD) were assessed for different powertrain technologies in 2024, 2035, and 2050, considering anticipated technological advancements. The analysis employed simulation models that accurately reflect vehicle dynamics, powertrain components, and energy storage systems, leveraging real-world driving data. An integrated simulation workflow was implemented using Argonne National Laboratory's POLARIS, SVTrip, Autonomie, and TechScape software. Additionally, a sensitivity analysis was performed to assess how fluctuations in energy and fuel costs impact the cost-effectiveness of various powertrain options. By 2035, battery electric trucks (BEVs) demonstrate strong cost competitiveness in the 0-250 mile and 250-500 mile ranges, especially when
Mansour, CharbelBou Gebrael, JulienKancharla, AmarendraFreyermuth, VincentIslam, Ehsan SabriVijayagopal, RamSahin, OlcayZuniga, NataliaNieto Prada, DanielaAlhajjar, MichelRousseau, AymericBorhan, HoseinaliEl Ganaoui-Mourlan, Ouafae
It is a fool's errand to make timely comments - in print! - about our current political turmoil. Even so, it feels important to place a marker in the sand to note the ongoing political reign of tariff threats, the upheaval potential of a demolished regulatory state affecting road and vehicle safety, and the damage that cuts to electric vehicle support might do to American automakers attempting to keep technological pace with their global automaker peers. It's a lot. The mainstream press is reporting the broad strokes of the industry's reaction to the new president. Ford CEO Jim Farley said Trump's erratic threats and changes are adding “a lot of cost and a lot of chaos” to the automotive industry and that a 25% tariff would “blow a hole in the U.S. industry that we've never seen.” Volvo Cars CEO Jim Rowan said that profitability would suffer under any tariffs, whether those are the general 25% tariffs on Canada and Mexico (now seemingly canceled after Trump backed down), just-announced
Blanco, Sebastian
Shared autonomous vehicles systems (SAVS) are regarded as a promising mode of carsharing service with the potential for realization in the near future. However, the uncertainty in user demand complicates the system optimization decisions for SAVS, potentially interfering with the achievement of desired performance or objectives, and may even render decisions derived from deterministic solutions infeasible. Therefore, considering the uncertainty in demand, this study proposes a two-stage robust optimization approach to jointly optimize the fleet sizing and relocation strategies in a one-way SAVS. We use the budget polyhedral uncertainty set to describe the volatility, uncertainty, and correlation characteristics of user demand, and construct a two-stage robust optimization model to identify a compromise between the level of robustness and the economic viability of the solution. In the first stage, tactical decisions are made to determine autonomous vehicle (AV) fleet sizing and the
Li, KangjiaoCao, YichiZhou, BojianWang, ShuaiqiYu, Yaofeng
This research explores the use of salt gradient solar ponds (SGSPs) as an environmentally friendly and efficient method for thermal energy storage. The study focuses on the design, construction, and performance evaluation of SGSP systems integrated with reflectors, comparing their effectiveness against conventional SGSP setups without reflectors. Both experimental and numerical methods are employed to thoroughly assess the thermal behavior and energy efficiency of these systems. The findings reveal that the SGSP with reflectors (SGSP-R) achieves significantly higher temperatures across all three zones—Upper Convective Zone (UCZ), Non-Convective Zone (NCZ), and Lower Convective Zone (LCZ)—with recorded temperatures of 40.56°C, 54.2°C, and 63.1°C, respectively. These values represent an increase of 6.33%, 11.12%, and 14.26% over the temperatures observed in the conventional SGSP (SGSP-C). Furthermore, the energy efficiency improvements in the UCZ, NCZ, and LCZ for the SGSP-R are
J, Vinoth Kumar
Soft skin coverings and touch sensors have emerged as a promising feature for robots that are both safer and more intuitive for human interaction, but they are expensive and difficult to make. A recent study demonstrates that soft skin pads doubling as sensors made from thermoplastic urethane can be efficiently manufactured using 3D printers.
This paper presents the strategy design, development, and detailed simulation of an Energy Management System (EMS) for a range extender energy storage microgrid project. Initially, a microgrid system model including photovoltaic (PV) and energy storage devices was established. Secondly, the Latin Hypercube Sampling (LHS) method was employed to generate possible operational scenarios, and an improved K-means clustering algorithm was used for scenario classification. Subsequently, a series of constraints were constructed for the economic viability of the microgrid to minimize its annualized comprehensive cost, while satisfying power balance and equipment operation. Finally, the microgrid system was simulated and solved using the GUROBI solver, covering cost analyses of the energy storage system and diesel generators under different configurations, as well as the State of Charge (SOC) variations of the energy storage system. The simulation results indicate that, after considering the one
Hua, YuweiJin, ZhenhuaHuang, HuilongWang, Zihao
This study introduces the Total Cost of Ownership per Unit Operating Time (TCOP) as a novel indicator to assess the economic impact of vehicle durability. A comprehensive analysis is conducted for fuel cell vehicles (FCVs), battery electric vehicles (BEVs), and internal combustion engine vehicles (ICEVs) in light- and heavy-duty scenarios. The results show that in HDVs, the advantages of low prices for hydrogen and electricity are fully demonstrated due to their high durability. In contrast, for LDVs, the purchase cost plays a much larger role, accounting for 68% of the total cost, indicating a significant difference between vehicles. Improving durability can significantly enhance the competitiveness of FCVs. For FCVs, increasing the durability from the current levels of 150,000 km for LDVs and 600,000 km for HDVs to 20,8500 km and 1,122,000 km, respectively, would align their TCOP with that of current ICEVs. A sensitivity analysis shows that for HDVs. The focus should be placed on
Qin, ZhikunYin, YanZhang, FanYao, JunqiGuo, TingWang, Bowen
The transition from internal combustion engine (ICE) industry to electric vehicle (EV) industry has significant financial implications for both the automotive industry, government, and associated partners. The shift to EVs could lead to savings in foreign exchange reserves, the creation of new jobs, and a reduction in greenhouse gas emissions. However, the transition could also result in job losses in the automobile and its associated manufacturing industry. This study aims to analyze the impact of this transition on different stakeholders in India. The study takes into account the different financial aspects that includes production, technology, government policy, skilling, employability, job creation, and other associated aspects on Indian economy. For the projected study different cases were considered with 2030 as the projected year with 30% EVs. A modest attempt is made to analyze the impact on associated partners. The findings of the study suggest that the transition to EVs could
Vashist, DevendraMalik, VarunPandey, Sachchidanand
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also
Oliveira Neto, Raimundo ArraisSouza, Camila Gomes PeçanhaBrito, Luis Roberto BonfimGuimarães, Georges Louis Nogueira
The future of wireless technology - from charging devices to boosting communication signals - relies on the antennas that transmit electromagnetic waves becoming increasingly versatile, durable and easy to manufacture. Researchers at Drexel University and the University of British Columbia believe kirigami, the ancient Japanese art of cutting and folding paper to create intricate three-dimensional designs, could provide a model for manufacturing the next generation of antennas. Recently published in the journal Nature Communications, research from the Drexel-UBC team showed how kirigami - a variation of origami - can transform a single sheet of acetate coated with conductive MXene ink into a flexible 3D microwave antenna whose transmission frequency can be adjusted simply by pulling or squeezing to slightly shift its shape.
North American automakers and EV battery firms have five years to erase China's dominance in technology and manufacturing or they may face the reality of buying batteries from China for the foreseeable future. That was the message from battery-analysis company Voltaiq CEO Tal Sholklapper at a media briefing in Detroit. “We're in the final innings now,” Sholklapper said. “If the industry around batteries and electric vehicles and all the follow-on applications wants to make it, we're going to have to change the way we play.”
Clonts, Chris
This study aims to explore the multifaceted influencing factors of market acceptance and consumer behavior of low-altitude flight services through online surveys and advanced neuroscientific methods (such as functional magnetic resonance imaging fMRI, electroencephalography EEG, functional near-infrared spectroscopy fNIRS) combined with artificial intelligence and video advertisement quantitative analysis. We conducted an in-depth study of the current trends in low-altitude flight vehicle development and customer acceptance of low-altitude services, focusing particularly on the survey methods used for market acceptance. To overcome the influence of strong opinion leaders in volunteer group experiments, we designed specialized surveys targeting broader online and social media groups. Utilizing specialized knowledge in aviation psychology, we designed a distinctive questionnaire and, within just 7 days of its launch, gathered a significant number of valid responses. The data was then
Ma, XinDing, ShuitingLi, Yan
Vehicle electrification has gained prominence in various industries and offers sustainability opportunities, especially in the context of heavy-duty vehicles such as school buses. Despite the prevalence of conventional diesel school buses (CDSB), the adoption of electric school bus (ESB) and other eco-friendly alternatives is increasing. In the United States alone, there has been a notable increase in the adoption of ESBs, indicating substantial growth. The electrification of school buses not only promises energy savings, but also offers health benefits to children, reduced greenhouse gas emissions, and environmentally friendly transportation practices, aligned with broader eco-friendly initiatives. This paper investigates the potential for energy savings and reduction in environmental footprint through electrification of school buses in the Columbus, OH area. Analyzing current bus routes and road terrain data allows one to estimate energy demand and environmental impact, accounting
Moon, JoonHanif, AtharAhmed, Qadeer
In vehicle Noise Vibration Harshness (NVH) development, vibroacoustic simulations with Finite Element (FE) Models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time the need for multiple evaluations of the same model with different input parameters – e.g., for uncertainty quantification, optimization, or robustness investigation – is also increasing. Therefore, it is crucial to reduce the computational costs dramatically in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations with varying parameters. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach. In Gaussian Process regression there are important
Luegmair, MarinusDantas, RafaellaSchneider, FelixMüller, Gerhard
Dynamic wireless charging (DWC) systems can make up electrified roads (eRoads) on which electricity from the grid is supplied to electric vehicles (EVs) wirelessly while the EVs travel along the roads. Electrification of roads contributes to decarbonizing the transport sector and offers a strong solution to high battery cost, range anxiety, and long charging times of EVs. However, the DWC eRoads infrastructure is costly. This article presents a model to minimize the infrastructure cost so that the deployment of eRoads can be economically more feasible. The investment for eRoad infrastructure consists of the costs of various components including inverters, road-embedded power transmitter devices, controllers, and grid connections. These costs depend on the traffic flow of EVs. The configuration and deployment strategy of the proposed eRoads in Southeastern Canada are designed with optimized charging power and DWC coverage ratio to attain the best cost-effectiveness. Well-designed
Qiu, KuanrongRibberink, HajoEntchev, Evgueniy
An SAE white paper on the different engineering approaches taken by traditional automakers and recent arrivals indicates that each category is remarkably aware of the others' strengths and weaknesses. Sven Beiker, a management lecturer at Stanford University, authored the report “Two Approaches to Mobility Engineering.” He gathered commentary from every corner of the vehicle ecosystem, from suppliers to software companies to manufacturers, and summarized the findings in a presentation at WCX 2024 in Detroit. Rather than “old companies,” Beiker likes to refer to traditional automakers as “incumbents.” Here are a few common observations from the report, which will be published this summer: Newer players are better at simplifying complexity, such as Tesla's ability to build vehicles with fewer parts. Older automakers are better at managing complexity, such as integrating disparate systems. Newer companies are constrained by financial resources and a shortage of available talent
Clonts, Chris
Quantum computing and its applications are emerging rapidly, driving excitement and extensive interest across all industry sectors, from finance to pharmaceuticals. The automotive industry is no different. Quantum computing can bring significant advantages to the way we commute, whether through the development of new materials and catalysts using quantum chemistry or improved route optimization. Quantum computing may be as important as the invention of driverless vehicles. Emergence of Quantum Computing Technologies in Automotive Applications: Opportunities and Future Use Cases attempts to explain quantum technology and its various advantages for the automotive industry. While many of the applications presented are still nascent, they may become mainstream in a decade or so. Click here to access the full SAE EDGETM Research Report portfolio.
Kolodziejczyk, Bart
Vehicle quality and affordability will always be the most distinguishing summative characteristics in a fully saturated and highly competitive market. While vehicle quality differentiates between brands in any market segment, affordability remains the key decisive factor for many buyers in each segment. Equally important, affordability is a critical factor in achieving equity in transportation by providing reasonably priced vehicles with quality fitting the needs of different users. Keeping in mind that the cost of quality is usually in conflict with affordability, the main challenge during the different phases of the vehicle design and development process from inception to production becomes the achievement of the multi-objective conflicting goals of maximizing affordability and quality at the same time. In this paper, guided by quality characteristics framework, that accounts for affordability as a context and structured participation of the customers during the vehicle realization
El-Sayed, Mohamed
Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods. The first is the virtual chip test
Jan, JamesKhorran, AaronHall, MarkTorcellini, SabrinaDoody, David
To promote real time monitoring, In use performance ratio monitoring “IUPRm” checks has been enforced in India from Apr’23 as a part of BS6-2 regulation. Since IUPRm is representative of diagnostic frequency in real driving conditions and usage pattern. therefore, a clear understanding of real-world driving is required to define IUPRm targets. This paper shares methodology and Validation steps for defining IUPRm routes for Indian market. Methodology objective is to standardize the market operating conditions over a particular region. Selected Methodology consist of three steps: For defining IUPRm route framework, first step is to have a pre-market survey to know current In use performance ratio “IUPR” status and improvement areas in existing market vehicles. Second step is to define market representative localized on road routes based on the finding of Pre-market survey. Third step is to validate defined IUPR routes and correlate the output in reference to coverage of market operating
Sharma, PrashantSingh, DilbaghKumar, AmitGautam, AmitKhanna, Vikram
Abstract 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. Annual distance traveled, battery replacement assumptions, and fuel
Kumar, DeepakAbdul-Manan, Amir F. N.Kalghatgi, GautamAgarwal, Avinash Kumar
The demand for electric vehicles (EVs) has been steadily increasing in recent years, led by the factors like environmental concerns, government incentives, and improvements in EV technology. The EV’s growth is expected to increase in the coming years as EVs become more affordable and more models become available on the market. Predicting the price of electric vehicles provides valuable insights on the EV market and inform a range of business, consumer, financial, and policy decisions. Predicting the price of electric vehicles using simple linear regression involves building a linear regression model with a single independent variable usually the vehicle’s characteristics or features to predict the dependent variable the price.This work has predicted the price of Electric Vehicle using a data set prepared for the Indian context. It has been predicted that there is significant correlation between battery capacity in Ah and the vehicle price. The measured RMSE value is 26274.942642891292
Raj, Joshua DanielImmanuel, J. SamsonKarthik, P.Jayanthi, M.
Harvard researchers have realized a key milestone in the quest for stable, scalable quantum computing, an ultra-high-speed technology that will enable game-changing advances in a variety of fields, including medicine, science, and finance.
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. Results show plug
Mittal, VikramShah, Rajesh
Climate change due to global warming calls for more fuel-efficient technologies. Parallel Full hybrids are one of the promising technologies to curb the climate change by reducing CO2 emissions significantly. Different parallel hybrid electric vehicle (HEV) architectures such as P0, P1, P2, P3 and P4 are adopted based on different parameters like fuel economy, drivability, performance, packaging, comfort and total cost of ownership of the vehicle. It is a great challenge to select right hybrid architecture for different vehicle segments. This paper compares P2 and P3 HEV with AMT transmission to evaluate most optimized architecture based on vehicle segment. Vehicles selected for study are from popular vehicle segments in India with AMT transmission i.e. Entry segment hatch and Compact SUV. HEV P2 and P3 architectures are simulated and studied with different vehicle segments for fuel economy, performance, drivability and TCO. The analyzed simulation results reveal similar fuel economy
Jadhav, Vaibhav V.Warule, Prasad B.
In recent years due to significant increased cost of raw material, fuel and energy, vehicle cost is increased. As vehicle cost is one of the major factors that attracts prospective buyers, it has created specific demand for low weight and low-cost components than traditional components with better performance to meet customer expectations. Suspension is one of the critical aggregates where lot of material is used and reduction in weight tends to give lot of cost benefit. As suspension system derives vehicle’s handling performance, it has to be ensured that handling performance of vehicle is maintained the same or made better while reducing weight of the suspension. Advancements in simulation capabilities coupled with manufacturing technology has enabled development non-traditional leaf springs. One of such springs is mono-leaf spring without shackle. This type of leaf spring provides advantages such as low weight and nonlinear stiffness. Hence, this type of spring can cater the need of
Pandhare, Vinay RamakantTiwari, ChaitanyaDeore, YogeshKhandekar, Dhiraj
To promote real time monitoring, IUPRm checks has been enforced in India from Apr’23 as a part of BS6-2 regulation. Since IUPRm monitoring is representative of diagnostic frequency in real driving conditions and usage pattern. Therefore, a clear understanding of real-world driving is required to define IUPRm targets. This paper shares methodology and Validation steps for defining IUPR routes for Indian market. Methodology objective is to standardize the market operating conditions over a particular region. Selected Methodology consist of three steps: For defining IUPR route framework, first step is to have a pre-market survey to know current IUPR status and improvement areas in existing market vehicles. Second step is to define market representative localized on road routes based on the finding of Pre-market survey. Third step is to validate defined IUPR routes and correlate the output in reference to coverage of market operating conditions. Routes definition (Step 2) starts with
Sharma, PrashantSingh, DilbaghKumar, AmitGautam, AmitKhanna, Vikram
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