Browse Topic: Product development

Items (3,915)
A consequence of the automotive industry's shift to electrification is that a significantly higher percentage of a vehicle's lifecycle CO2 emissions occur during the production phase. As a result, vehicle manufacturers and suppliers must shift the focus of product development from the 'in-use phase only' to optimizing the complete product lifecycle. The proper design of a battery has the highest impact to all other phases following in the life cycle. It influences the selection of materials, the manufacturing, in-use and end of life, respectively the recycling and recycling yield for a circular economy. Using real-life examples, the paper will explain what the main parameters are necessary for designing a sustainable battery. What are the low hanging fruits to be considered? In addition, it will elaborate on the relation as well as the impacts to other KPIs like safety, costs and lifetime of the battery. Finally, it will round up in an outlook on how batteries will evolve in the future
Braun, AndreasRothbart, Martin
The unsteady wind conditions experienced by a vehicle whilst driving on the road are different to those typically experienced in the steady-flow wind tunnel development environment, due to turbulence in the natural wind, moving through the unsteady wakes of other road vehicles and travelling through the stationary wakes generated by roadside obstacles. This paper presents an experimental approach using a large SUV-shaped vehicle to assess the effect of unsteady wind on the modulated noise performance, commonly used to evaluate unsteady wind noise characteristics. The contribution from different geometric modifications were also assessed. The approach is extended to assess the pressure distribution on the front side glass of the vehicle, caused by the aerodynamic interactions of the turbulent inflow in straight and yawed positions, to provide insight into the noise generation mechanisms and differences in behaviour between the two environments. The vehicle response to unsteady wind
Jamaluddin, Nur SyafiqahOettle, NicholasStaron, Domenic
A cutting-edge EV powertrain NVH laboratory has been established at Dana Incorporated’s world headquarters in Ohio, significantly enhancing its capabilities in EV powertrain NVH development. This state-of-the-art, industry-leading facility is specifically designed to address diverse NVH requirements for EV powertrain development and validation processes. This capability substantially reduces development time for new drivetrain systems. Key features of the laboratory include a hemi-anechoic chamber, two AC asynchronous load motors, an acoustically isolated high-speed input motor, and two battery emulators capable of accommodating both low and high-voltage requirements. The NVH laboratory enables engineers to evaluate system performance and correlate results with digital twin models. This capability supports the optimization of NVH characteristics at both the system and component levels, as well as the refinement of CAE models for enhanced design precision. This paper details the design
Cheng, Ming-TeZugo, Chris
Heavy Duty (HD) linehaul vehicles are majorly used in transportation of goods and heavy loads between different cities or long distances. Considering the current trend, payload capacity of these heavy-duty trucks are increasing due to constant increase in the load demand. Due to which engine torques of these HD vehicles are increasing which in turn increases the transmission input torque. At higher torque levels, gear excitation also increases and transmission becomes more susceptible towards higher noise radiation. The transmission is an integral part of the driveline in a heavy duty commercial vehicle. Along with speed and torque conversion, the transmission design is crucial to achieve better fuel economy. Important factors to consider in the transmission design are duty cycle, torque capacity, fuel economy and overall weight. Global vehicle pass-by noise regulations for HD commercial vehicles are becoming more stringent and transmissions are expected to be very quiet. Historically
Rastogi, SarthakMilind, T. R.
Reducing gear rattle noise within the passenger cabin is a crucial objective in vehicle development due to its direct impact on customer comfort and driving experience. Gear rattle occurs when free gears collide during meshing, primarily driven by high torsional vibrations generated by engine fluctuations. These vibrations are transmitted through the clutch system to the transmission, amplifying noise inside the cabin. This study focuses on optimizing the clutch by stabilizing its hysteresis to address this issue. This helps minimize the torsional vibrations transferred to the transmission input shaft, thereby reducing gear rattle. The investigation centers on a case where significant gear rattle was observed at high vehicle speeds, particularly under high engine torque conditions. A thorough root cause analysis identified that the primary contributor to the noise was a drop in the clutch hysteresis value at elevated engine torques. This drop increased torsional vibrations in the
Awasthi, MradulDhankhar, Dinesh SinghKhare, Devendra KumarRana, DeepakPandey, Anant
Sound source identification based on beamforming is widely used today as a spatial sound field visualization technology in wind tunnel experiments for vehicle development. However, the conventional beamforming technique has its inherent limitation, such as bad spatial resolution at the low frequency range, and limited system dynamic range. To improve the performance, three deconvolution methods CLEAN, CLEAN-SC and DAMAS were investigated and applied to identify wind noise sources on a production car in this paper. After analysis of vehicle exterior wind noise sources distribution, correlation analysis between identified exterior noise sources and interior noise were conducted to study their energy contribution to vehicle interior. The results show that the algorithm CLEAN-SC based on spatial source coherence shows the best capability to remove the sidelobes for the uncorrelated wind noise sources, while CLEAN and DAMAS, which are based on point spread functions have definite
He, YinzhiShen, HenghaoWu, YuZhang, LijunYang, ZhigangBlumrich, ReinhardWiedemann, Jochen
For mature virtual development, enlarging coverage of performances and driving conditions comparable with physical prototype is important. The subjective evaluation on various driving conditions to find abnormal or nonlinear phenomena as well as objective evaluation becomes indispensable even in virtual development stage. From the previous research, the road noise had been successfully predicted and replayed from the synthesis of system models. In this study, model based NVH simulator dedicated to virtual development have been implemented. At first, in addition to road noise, motor noise was predicted from experimental models such as blocked force and transfer function of motor, mount and body according to various vehicle conditions such as speed and torque. Next, to convert driver’s inputs such as acceleration and brake pedal, mode selection button and steering wheel to vehicle’s driving conditions, 1-D performance model was generated and calibrated. Finally, the audio and visual
Park, SangyoungDirickx, TomKang, Yeon JuneNam, Jeong MinGonçalves, Vinícius Valencia
Platform based vehicle development is standardized at John Deere. The challenges of frontloading the integration of individual components within different platforms using predictive methods is key to shortening the development cycle. Components are individually characterized on test benches and results cannot directly be used to evaluate system performance. Invariant characterization is needed instead, which is possible through techniques such as blocked loads estimation. To evaluate the applicability of such methods, the component-based loads and vehicle in-situ operational loads need to be compared. The confident use of these methods for obtaining structural and acoustic loads enables the use of hybrid system models, enhancing early NVH response predictions. The objective of this work was to enable the confident use of test stand measurements in predictive models across various vehicle platforms. This study compares a powertrain characterization in a vehicle against a test stand to
Vesikar, Prasad BalkrishnaEdgington, JasonDrabison II, John
As India’s economy expands and road infrastructure improves, the number of car owners is expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines. Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development
Rai, NiteshMehta, MakrandRavindran, Mugundaram
There are some paradoxical keys to NVH engineering success that are not taught in engineering schools. This paper will describe these in detail and provide examples to add context. The first unexpected key is that a good generalist makes a better expert. The more you understand the complete product development process, and the better contacts you have throughout the product development organization, the easier it will be for you to find cost effective solutions to your specific issues. Next, you need to know your customers, and that means both internal and external customers. If you work for a supplier, it means knowing original equipment manufacturer (OEM) and end user customers. The more you understand the customers’ needs, the better you can address them and make your product stand out. Another key is to try to turn a crazy idea into something practical. Sometimes you might find a completely insane solution to your problem, such as making a major component out of solid gold. If you
Reinhart, Thomas
A test and signal processing strategy was developed to allow a tire manufacturer to predict vehicle-level interior response based on component-level testing of a single tire. The approach leveraged time-domain Source-Path-Contribution (SPC) techniques to build an experimental model of an existing single tire tested on a dynamometer and substitute into a simulator vehicle to predict vehicle-level performance. The component-level single tire was characterized by its acoustic source strength and structural forces estimated by means of virtual point transformation and a matrix inversion approach. These source strengths and forces were then inserted into a simulator vehicle model to predict the acoustic signature, in time-domain, at the passenger’s ears. This approach was validated by comparing the vehicle-level prediction to vehicle-level measured response. The experimental model building procedure can then be adopted as a standard procedure to aid in vehicle development programs.
Nashio, HiroshiKajiwara, KoheiRinaldi, GiovanniSakamoto, Yumiko
Compressed Natural Gas (CNG) engines are emerging as a viable alternative to gasoline and diesel in heavy commercial and passenger transport worldwide. They offer reduced CO₂ emissions and support energy independence in regions rich in natural gas. In India, enhanced CNG infrastructure and strict emission regulations have driven OEMs to develop CNG vehicles across all segments. Moreover, from a noise and vibration standpoint, CNG vehicles are expected to deliver cabin refinement comparable to that of their fossil fuel counterparts. However, one of the major challenges associated with CNG vehicles is the excitation due to additional components like CNG Pressure Regulator, Injector et al. The operational metallic/pulsation noises are generally higher as compared to liquid fuels like gasoline due to dry nature of the CNG fuel. This paper describes in detail the pulsation noise phenomena encountered during one of the late-stage vehicle development projects. An experimental root cause
Chatterjee, JoydeepRavindran, Mugundaram
Tires have a significant impact on vehicle road noise. The noise in 80~160Hz is easily felt when driving on rough roads and has a great relationship with the tire structural design. How to improve the problem through tire simulation has become an important issue. Therefore, this paper puts forward the concept of virtual tire tuning to optimize the noise. An appropriate tire model is crucial for road noise performance, and the CDtire (Comfort and Durability Tire) model was used in the article. After conducting experimental validation to get an accurate tire model, adjust the parameters and structure of the tire model to generate alternative model scenarios. The transfer function of the tire center was analyzed and set as the evaluation condition for tire NVH (Noise, vibration, and harshness) performance. This enabled a comparison among various model scenarios to identify the best-performing tire scenario in focused frequency whose transfer function needed to be lowest. Manufacture the
Zhang, BenYu Sr, JingChen, QimiaoLiu, XianchenGu, Perry
During cylinder deactivation events, high amplitude torque pulsations are generated at the crankshaft of the engine over a wide frequency range creating a potential risk for noise, vibration and harshness (NVH) performance of the vehicle. As passive tuned mass dampers are effective only in a narrow frequency range, active tuned mass dampers (ATMD) have become a popular choice to mitigate the risk. Often, engineers rely on finite element (FE) models of vehicle structures to make design decisions during the early stages of vehicle development. However, there is limited literature on the simulation of ATMD using FE techniques. Consequently, several details related to the ATMD design are decided through physical testing at the latter stages of vehicle development which is not ideal. To address these issues, a novel methodology to simulate an ATMD during cylinder deactivation events using FE technique is presented here. In this study, an ATMD based on force feedback control method was
Maddali, RamakanthMogal, Akbar BaigHaider, SyedJahangir, Yawar
The multifaceted, fast-paced evolution in the automotive industry includes noise and vibration (NVH) behavior of products for regulatory requirements and ever-increasing customer preferences and expectations for comfort. There is pressing need for automotive engineers to explore new and advanced technologies to achieve a ‘First Time Right’ product development approach for NVH design and deliver high-quality products in shorter timeframes. Artificial Intelligence (AI) and Machine Learning (ML) are trending transformative technologies reshaping numerous industries. AI enables machines to replicate human cognitive functions, such as reasoning and decision-making, while ML, a branch of AI, employs algorithms that allow systems to learn and improve from data over time. The purpose of the paper is to show an approach of using machine learning techniques to analyze the impact of variations in structural design parameters on vehicle NVH responses. The study begins by executing the Design of
Miskin, Atul R.Parmar, AzanRaj, SoniaHimakuntla, Uma Maheswar
In the era of Industry 4.0, the maintenance of factory equipment is evolving with new systems using predictive or prescriptive methods. These methods leverage condition monitoring through digital twins, Artificial Intelligence, and machine learning techniques to detect early signs of faults, types of faults, locations of faults, etc. Bearings and gears are among the most common components, and cracking, misalignment, rubbing, and bowing are the most common failure modes in high-speed rotating machinery. In the present work, an end-to-end automated machine learning-based condition monitoring algorithm is developed for predicting and classifying internal gear and bearing faults using external vibration sensors. A digital twin model of the entire rotating system, consisting of the gears, bearings, shafts, and housing, was developed as a co-simulation between MSC ADAMS (dynamic simulation tool) and MATLAB (Mathematical tool). The gear and bearing models were developed mathematically, while
Rastogi, SarthakSinghal, SrijanAhirrao, SachinMilind, T. R.
This paper discusses a systematic process that was developed to evaluate the acoustic performance of a production dash system. In this case it is for an electric vehicle application. The production dash panel was tested under different configurations to understand the importance of passthroughs in the acoustics of the system. Results show that often the performance of the passthroughs strongly affects the overall performance of the dash system and this may become the limiting factor to increase the system sound transmission loss. To understand the acoustic strength of different passthroughs and their effects on the overall system, the dash with passthroughs underwent extensive testing. Subsequently, a test procedure using flat panels was developed to quantify the performance of individual passthroughs on a part level. This data can be used by the OEM to develop STL targets that can be considered in the grommet design early in the vehicle development process.
Saha, PranabBaack, GregoryGeissler, ChristianKaluvakota, SrikanthPilz, Fernando
The aircraft cabin plays a crucial role in airline differentiation strategies, particularly when introducing novel, data-driven services. These services aim to enhance the passenger experience during the flight and to improve cabin crew efficiency in order to reduce workload and ensure continued growth of airline revenue. Digitalization and extensive exchange of information across the entire aircraft transport system have emerged as key enablers for these services. The development of aircraft and aircraft systems that realize these services is characterized by a multi-level development process. Various development levels are considered to initially identify the functions of an aircraft in the air transport system, refine its systems and break them down into their components until a level of detail is reached that allows the implementation of the component functions. In addition to the high complexity, a major challenge in this development is to ensure traceability and consistency
Blecken, MarvinHintze, HartmutGiertzsch, FabianGod, Ralf
Airworthiness certification of aircraft requires an Airworthiness Security Process (AWSP) to ensure safe operation under potential unauthorized interactions, particularly in the context of growing cyber threats. Regulatory authorities mandate the consideration of Intentional Unauthorized Electronic Interactions (IUEI) in the development of aircraft, airborne software, and equipment. As the industry increasingly adopts Model-Based Systems Engineering (MBSE) to accelerate development, we aim to enhance this effort by focusing on security scope definitions – a critical step within the AWSP for security risk assessment that establishes the boundaries and extent of security measures. However, our findings indicate that, despite the increasing use of model-based tools in development, these security scope definitions often remain either document-based or, when modeled, are presented at overly abstract levels, both of which limit their utility. Furthermore, we found that these definitions
Hechelmann, AdrianMannchen, Thomas
Increasing digitalization of the aircraft cabin, driven by the need for improved operational efficiency and an enhanced passenger experience, has led to the development of data-driven services. In order to implement these services, information from different systems is often required, which leads to a multi-system architecture. When designing a network that interconnects these systems, it is important to consider the heterogeneous device and supplier landscape as well as variations in the network architecture resulting from airline customization or cabin upgrades. The novel ARINC 853 Cabin Secure Media-Independent Messaging (CSMIM) standard addresses this challenge by specifying a communication protocol that relies on a data model to encode provided and consumed information. This paper presents an approach to integrate CSMIM-specific communication concepts into a Model-Based Systems Engineering (MBSE) framework using the Systems Modeling Language (SysML). This enables a streamlined
Giertzsch, FabianBlecken, MarvinGod, Ralf
The authors have witnessed a notable surge in the number of designs and in the guidance material for electric and hybrid aircraft. FAA and EASA have continued to evaluate the safety of Propulsion Battery Systems (PBS), with a focus on thermal runaway containment testing. As a result, a harmonization white paper [7] was issued to provide a certification path for Thermal Runaway (TR) Hazards, followed by an EASA certification memorandum on the acceptable approaches for the certification of Electric/Hybrid Propulsion Systems (EHPS). Recently, an FAA Advisory Circular (draft) was issued for the “powered-lift” aircraft that feature these propulsion battery systems. Despite the advances made by electric/hybrid aircraft manufacturers and the aviation authorities, there is still a missing piece of the puzzle. Mainly, engineering work still needs to be done to properly integrate the EHPS architecture to achieve safety objectives. The burden is still on systems engineering to propose their own
Hanna, MichaelWalker, Cherizar
Helicopter vibrations, primarily generated by the main rotor-gearbox assembly, are a major source of concern due to their impact on structural integrity, cockpit instrument durability, and crew comfort. These vibrations are mainly transmitted through the gearbox’s rigid support struts to the fuselage, leading to increased cabin noise and potential damage to critical components. This paper presents a solution for vibration mitigation which involves replacing traditional gearbox support struts with low-weight, high-performance active dampers. Developed by Elettronica Aster S.p.A., these active dampers are designed as electro-hydraulic actuators embedded within a compliant structure. The parallel nested configuration of the system enables high power densities and effective vibration control, significantly reducing the transmission of harmful vibrations to the fuselage. The comprehensive model-based design process is detailed, describing the development and use of a high-fidelity physics
Bertolino, Antonio CarloSorli, MassimoPorro, Paolo GiovanniGalli, Claudio
The two-wheeler industry features a diverse range of transmission systems catering to varied riding preferences and market demands. Manual transmissions offer direct gear control, favored by enthusiasts for its precision and customizable performance. Automatic transmissions simplify riding, especially in urban settings, eliminating manual gear shifts and reducing rider fatigue. Understanding the dynamics of transmission systems in the two-wheeler space is crucial for manufacturers, engineers, policymakers, and riders alike. It informs product development, regulatory compliance efforts, and market positioning initiatives in an increasingly competitive and innovation-driven industry landscape. DCT (Dual Clutch Transmission) and manual transmissions represent extremes in rider engagement, automation, and cost. While DCT offers seamless gear changes and convenience at a higher price point, manual transmissions provide direct control and a tactile experience with lower initial costs. Riders
Kundu, Prantik
Hybrid powertrain for motorcycles has not been widely adopted to date but has recently shown significant increased interest and it is believed to have great potential for fuel economy containment in real driving conditions. Moreover, this technology is suitable for the expected new legislations, reduced emissions and enables riding in Zero Emissions Zones, so towards a more carbon neutral society while still guaranteeing “motorcycle passion” for the product [1, 2]. Several simulation tools and methods are available for the concept phase of the hybrid system design, allowing definition of the hybrid components and the basic hybrid strategies, but they are not able to properly represent the real on-road behaviour of the hybrid vehicle and its specific control system, making the fine tuning and validation work very difficult. Motorcycle riders are used to expect instant significant torque delivery on their demand, that is not properly represented in legislative cycles (e.g. WMTC); rider
Antoniutti, ChristianSweet, DavidHounsham, Sandra
The rear swing arm, a crucial motorcycle component, connects the frame and wheel, absorbing the vehicle’s load and various road impacts. Over time, these forces can damage the swing arm, highlighting the need for robust design to ensure safety. Identifying potential vulnerabilities through simulation reduces the risk of failure during the design phase. This study performs a detailed fatigue analysis of the swing arm across different road conditions. Data for this research were collected from real-vehicle experiments and simulation analyses, ensuring accuracy by comparing against actual performance. Following CNS 15819-5 standards, road surfaces such as poorly maintained, bumpy, and uneven roads were tested. Using Motion View, a comprehensive multi-body dynamic model was created for thorough fatigue analysis. The results identified the most stress-prone areas on the swing arm, with maximum stress recorded at 109.6N on poorly maintained roads, 218.3N on bumpy surfaces, and 104.8N on
Chiou, Yi-HauHwang, Hsiu-YingHuang, Liang-Yu
This paper addresses the need for improved material selection in parcel shelves, a key component in passenger vehicles used to conceal the trunk area. The focus is on weight optimization, structural integrity, and perceived quality improvement using sustainable and ultra-lightweight composite materials. Traditional materials such as PET Woodstock, while durable, contribute significantly to vehicle weight, which is a drawback in the context of electric vehicles (EVs). The proposed composite material alternatives offer a high strength-to-weight ratio and have been shown to improve the load vs. deflection ratio, enhance aesthetics, and reduce manufacturing complexity and costs. This study outlines the testing and evaluation process of varying GSM and thicknesses of composite materials, demonstrating superior stiffness, reduced deflection under load, and enhanced ease of assembly. This work contributes to the ongoing efforts to achieve lightweighting, cost efficiency, and sustainability in
Kinthala, Nareen KumarPatnaik, MangaKhandelwal, MohitKakani, Phani KumarPalaniappan, Elavarasan
Physical testing is required to assess multiple vehicles in different conditions, specially to validate those related to regulations. The acoustic evaluations have difficulties and limitations in physical test; cost and time represent important considerations every time. Additionally, the physical validation happens once a prototype has been built, this takes place in a later phase of the development. Sound pressure is measured to validate different requirements in a vehicle, horn sound is one of these and it is related to a regulation of united nations (ECE28). Currently the validation happens in physical test only and the results vary depending on the location of the horn inside the front end of every vehicle. [7] In this article, the work for approaching a virtual validation method through CAE is presented with the intention to get efficiency earlier in product development process.
Alonso, LilianaCruz, RacielAlvarez, Ezequiel
Following early adoption, the BEV market has shifted towards a mass market strategy, emphasizing on crucial attributes, such as system cost reduction and range extension. System efficiency is crucial in BEV product development, where efficiency metric influenced greatly vehicle range and cost. For instance, higher iDM efficiency reduces the need for larger battery, cutting cost, or extends range with the same battery size. BorgWarner adopted Digital Twin technology to optimize Integrated Drive Module (iDM) within a vehicle ecosystem. Digital Twin comprises high-fidelity physics based numerical tool suites offering greater degree of freedom to engineers in designing, sizing, optimizing a component versus system benefit tradeoff, thus enabling most efficient product design within economic constraints. BorgWarner’s Analytical System Development (ASD) plan used as framework provides a global unified process for tool development and validation, ensuring the digital print of a real product
Bossi, AdrienBourniche, EricLeblay, ArnaudDavid, PascalNanjundaswamy, Harsha
Model-Based Systems Engineering (MBSE) enables requirements, design, analysis, verification, and validation associated with the development of complex systems. Obtaining data for such systems is dependent on multiple stakeholders and has issues related to communication, data loss, accuracy, and traceability which results in time delays. This paper presents the development of a new process for requirement verification by connecting System Architecture Model (SAM) with multi-fidelity, multi-disciplinary analytical models. Stakeholders can explore design alternatives at a conceptual stage, validate performance, refine system models, and take better informed decisions. The use-case of connecting system requirements to engineering analysis is implemented through ANSYS ModelCenter which integrates MBSE tool CAMEO with simulation tools Motor-CAD and Twin Builder. This automated workflow translates requirements to engineering simulations, captures output and performs validations. System
Upase, BalasahebShroff, Roopesh
The vehicle wake region is of high importance when analyzing the aerodynamic performance of a vehicle. It is characterized by turbulent separated flow and large low-pressure regions that contribute significantly to drag. In some cases, the wake region can oscillate between different modes which can pose an engineering challenge during vehicle development. Vehicles that exhibit bimodal wake behavior need to have their drag values recorded over a sufficient time period to take into account the low frequency shift in drag signal, therefore, simulating such vehicle configurations in CFD could consume substantial CPU hours resulting in an expensive and inefficient vehicle design iterations process. As an alternative approach to running simulations for long periods of time, the impact of adding artificial turbulence to the inlet on wake behavior and its potential impact on reduced runtime for design process is investigated in this study. By adding turbulence to the upstream flow, the wake
DeMeo, MichaelParenti, GuidoMartinez Navarro, AlejandroShock, RichardFougere, NicolasRazi, PooyanOliveira, DaniloLindsey, CraigYu, ChenxingBreglia Sales, Flavio
China Automotive Engineering Research Institute Co., Ltd (CAERI) has completed a new vehicle aero-acoustic wind tunnel (AAWT), which is located in Chongqing, China, and has been in operation for 5 years. To help addressing the Chinese vehicle market’s need to improve fuel economy, reduce exhaust emissions, and decrease product development period, the wind tunnel was designed and implemented to achieve a high degree of automation for vehicle testing next to a high aerodynamic and acoustic test accuracy for product development. The CAERI wind tunnel was in operation in June 2019, achieving a top speed of 250 km/h. A 5-belt rolling road system with a long center belt for proper wake simulation is installed inside, a test section with very low static pressure gradient and background noise. Wind tunnel calibration and customized measurement activities can be performed with an overhead traversing system. In the present paper, the main facilities of the AAWT are described next to necessary
Xu, LeiZhu, XijiaWang, QingyangBu, HanPeng, ChaoShi, FengYang, ChaoHuang, TaoZeng, YiZeng, XiangyiWallmann, SteffenMünstermann, HenningWittmeier, FelixMercker, EdzardBlumrich, Reinhard
Interest in Battery-Driven Electric Vehicles (EVs) has significantly grown in recent years due to the decline of traditional Internal Combustion Engines (ICEs). However, malfunctions in Lithium-Ion Batteries (LIBs) can lead to catastrophic results such as Thermal Runaway (TR), posing serious safety concerns due to their high energy release and the emission of flammable gases. Understanding this phenomenon is essential for reducing risks and mitigating its effects. In this study, a digital twin of an Accelerated Rate Calorimeter (ARC) under a Heat-Wait-and-Seek (HWS) procedure is developed using a Computational Fluid Dynamics (CFD) framework. The CFD model simulates the heating of the cell during the HWS procedure, pressure build-up within the LIB, gas venting phenomena, and the exothermic processes within the LIB due to the degradation of internal components. The model is validated against experimental results for an NCA 18650 LIB under similar conditions, focusing on LIB temperature
Gil, AntonioMonsalve-Serrano, JavierMarco-Gimeno, JavierGuaraco-Figueira, Carlos
This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the electric Lubrication Oil Pump (eLOP), a crucial component within a vehicle's powertrain system. The proposed eLOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the Digital Twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's lifecycle. The
Khan, JalalD'Alessandro, StefanoTramaglia, FedericoFauda, Alessandro
Over recent years, BorgWarner has intensified its efforts to explore and leverage trending technologies such as Artificial Intelligence (AI) and Machine Learning (ML) to enhance products and processes. This includes digital twin technology, which has potential use cases for system behavior analysis, product optimization and predictive maintenance. This paper outlines the development process of a digital twin for a commercial vehicle battery, which serves as a demonstrator and learning platform for this technology. In order to assess the feasibility as well as hard- and software requirements, a cloud-based digital twin demonstrator was developed, integrating vehicle telemetry data with physics-based battery electric and thermal models, and an aging prediction algorithm. The key components are an Internet of Things (IoT) gateway, simulation models, data processing and ingestion pipelines, a machine learning algorithm for anomaly detection, and visualizations of telemetry and simulation
Bongards, AnitaLiu, XiaobingBeemer, MariaGajowski, DanielRama, NeerajShah, KeyaFallahdizcheh, Amirhossein
In recent years, simulation-based performance of the models is a highly effective way to finalize the model at design stage itself. But simulation-based models are complex owing to more parameters involved hence resulting in more computational time. With the increasing demand for electric vehicles, the development time for electric vehicle (EV) powertrain is reduced, thereby increasing pressure on original equipment manufacturers (OEMs) to develop products faster. Digital twin is a platform where replication of physical models is made possible with extremely limited data to predict the performance of the model hence providing the most accurate results in a short time. Electric vehicles are the best alternatives for reducing emissions. An Electric vehicle is run by an electric motor which in turn is powered by a battery. Interior permanent magnet synchronous motors (IPMSMs) are the conventional type of motors in electric vehicles because of their high-power density and efficiency. This
Shroff, RoopeshUpase, Balasaheb
In the modern automotive industry, improving fuel efficiency while reducing carbon emissions is a critical challenge. To address this challenge, accurately measuring a vehicle’s road load is essential. The current methodology, widely adopted by national guidelines, follows the coastdown test procedure. However, coastdown tests are highly sensitive to environmental conditions, which can lead to inconsistencies across test runs. Previous studies have mainly focused on the impact of independent variables on coastdown results, with less emphasis on a data-driven approach due to the difficulty of obtaining large volumes of test data in a short period, both in terms of time and cost. This paper presents a road load energy prediction model for vehicles using the XGBoost machine learning technique, demonstrating its ability to predict road load coefficients. The model features 27 factors, including rolling, aerodynamic, inertial resistance, and various atmospheric conditions, gathered from a
Song, HyunseungLee, Dong HyukChung, Hyun
Electric vehicles rely on accurate estimation of battery states to operate safely and efficiently. Traditionally, the state estimation is pack level and based on empirical models developed to capture the dynamics of a representative battery pack and hence falls short in accounting for cell-to-cell variations. These variations become more pronounced as the cells age within a battery pack under non-homogeneous mechanical, thermal, manufacturing, and electrical conditions. It is challenging to adapt the traditional physics-based model to changing battery dynamics in real-time. To improve the state estimation at the cell level, a data-driven approach utilizing streamed data from vehicles enabled by connectivity has been shown in this paper. While traditional data-driven approaches result in large models and require large quantities of data for training, the proposed method relies on combining the underlying physics of the electrochemical model with novel data-driven modeling techniques
Gupta, ShobhitHegde, BharatkumarHaskara, IbrahimShieh, Su-YangChang, Insu
Automotive chassis components are considered as safety critical components and must meet the durability and strength requirements of customer usage. The cases such as the vehicle driving through a pothole or sliding into a curb make the design (mass efficient chassis components) challenging in terms of the physical testing and virtual simulation. Due to the cost and short vehicle development time requirement, it is impractical to conduct physical tests during the early stages of development. Therefore, virtual simulation plays the critical role in the vehicle development process. This paper focuses on virtual co-simulation of vehicle chassis components. Traditional virtual simulation of the chassis components is performed by applying the loads that are recovered from multi-body simulation (MBD) to the Finite Element (FE) models at some of the attachment locations and then apply constraints at other selected attachment locations. In this approach, the chassis components are assessed
Behera, DhirenLi, FanTasci, MineSeo, Young-JinSchulze, MartinKochucheruvil, Binu JoseYanni, TamerBhosale, KiranAluru, Phani
E-mobility is revolutionizing the automotive industry by improving energy-efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy-efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under
Ratz, FlorianBäuml, ThomasKompara, TomažKospach, AlexanderSimic, DraganJan, PetraMöller, SebastianFuse, HiroyukiParedes Barros, EstebanArmengaud, EricAmati, NicolaSorniotti, AldoLukesch, Walter
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