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This specification covers a corrosion-resistant steel in the form of investment castings homogenized and solution and precipitation heat treated to 180 ksi (1241 MPa) tensile strength.
AMS F Corrosion and Heat Resistant Alloys Committee
This study introduces a novel Large Language Model (LLM)-driven approach for comprehensive diagnosis and prognostics of vehicle faults, leveraging Diagnostic Trouble Codes (DTCs) in line with industry-standard automation protocols. The proposed model asks for significant advancement in automotive diagnostics by reasoning through the root causes behind the fault codes given by DTC document to enhance fault interpretability and maintenance efficiency, primarily for the technician and in few cases, the vehicle owner. Here LLM is trained on vehicle specific service manuals, sensor datasets, historical fault logs, and Original Equipment Manufacturer (OEM)-specific DTC definitions, which leads to context-aware understanding of the vehicle situation and correlation of incoming faults. Approach validation has been done using field level real-world vehicle dataset for different running scenarios, demonstrating model’s ability to detect complex fault chains and successfully predicting the
Pandey, SuchitJoshi, PawanKondhare, ManishCH, Sri RamGajbhiye, AbhishekS, Adm Akhinlal
Tire wear progression is a nonlinear and multi-factor degradation phenomenon that directly influences vehicle safety, handling stability, braking performance, rolling resistance, and fleet operational cost. Global accident investigations indicate that accelerated or undetected tread depletion contributes to nearly 30% of highway tire blowouts, highlighting the limitations of conventional wear indicators such as physical tread wear bars, mileage-based service intervals, and periodic manual inspections. These manual and threshold-based approaches fail to capture dynamic driving loads, compound ageing, pressure imbalance effects, or platform-specific wear behaviours, thereby preventing timely intervention in real-world conditions. This work presents an Indirect Tire Wear Health Monitoring System that employs an advanced Machine Learning + Transfer learning architecture to infer tread wear level and Remaining Useful Life (RUL) without relying on any tire-mounted sensors. The system ingests
Imteyaz, ShahmaIqbal, Shoaib
The invention tackles the main drawback of traditional electric vehicle charge ports which use Vehicle Control Unit (VCU) communication intensively and tend to have separate actuators to fulfill the locking function and requirements. These existing systems do not only limit autonomous operation of the charging lid in ignition-off condition but they also add mechanical complexity and packaging space, as well. To overcome these limitations, this research work introduces a Smart Charge Port Housing (CPH), which combines a rotary actuator with an onboard microcontroller and single shaft self-locking device, which allows intelligent and autonomous control of the flaps without relying on vehicle wide control networks. The actuator can remember the last position that the charging lid was in so it can be operated even while the VCU is in the inactive state. The integrated self-locking functionality is achieved by using a specially designed hinge shaft that allows a certain free play for
Mohunta, SanjayKhadake, Sagar
Artificial Intelligence and Machine learning models have a large scope and application in Automotive embedded systems. These models are used in the automotive world for various applications like calibration, simulation, predictions, etc. These models are generally very accurate and play the role of a virtual sensor. However, the AI/ML models are resource intensive which makes them difficult to execute on largely optimized automotive embedded systems. The models also need to follow safety standards like ASIL-D. The current work involves creating a Global DoE with ETAS ASCMO to generate data from a 125cc single to create AI/ML model for the engine outputs like Torque, T3, Mid-cat temperatures etc. The created models were validated across the operating space of the engine and found to have good accuracies. With ETAS Embedded AI Coder, the torque and T3 prediction AI models were converted to embedded code which can be easily used as a virtual sensor in real time. Using these AI models
Chouhan, Vineet SinghBulandani, SaurabhKumar, AlokVarsha, AnuroopaP R, Renjith
Meeting the stringent emissions norms of CEV stage V for medium BMEP engines, CI engines present significant challenges, particularly concerning cold startability. Low ambient temperatures and pressures intensify the cold start difficulties which are characterized by prolonged cranking, incidences of misfiring, compromised transient response and overall engine performance. This paper highlights the strategies and technologies employed to enhance cold start and transient performance of medium BMEP engines under such demanding environmental conditions. Investigations were conducted up to an altitude of 4500m and ambient temperatures as low as-20°C, utilizing only air heater at intake manifold as the sole cold start aid. This cost effective approach is integrated with an optimized combustion chamber design, along with minimal pilot injection timing and quantity to facilitate smooth ignition and stable combustion during cold start. The paper also explore the techniques to improve the
Saxena, HarshitLokare, PrasadSanthosh, AjithGandhi, NareshShinde, Prashant
The acquisition of road profile data is crucial for various automotive testing applications, including vehicle dynamics analysis, chassis endurance tests, and simulation of vehicle-road interactions. This is necessary for conducting virtual tests to accelerate research and development processes and can significantly reduce testing costs. However, most of the on-road measurements lack comprehensive and relevant road profile data. Conducting on-road trials to acquire this data is a laborious and time-consuming process, often impeded by logistical and environmental challenges. This research proposes a generative AI-based methodology for creating diverse and realistic road profile mixes from the existing on-road dataset of front axle displacement and road profile measured with a laser sensor. By leveraging advanced machine learning techniques, the proposed approach seeks to generate synthetic road profiles that accurately reflect real-world conditions, thereby reducing the dependency on
Rajappan, Dinesh KumarVenkatesh, Anirudh AnandR, SureshN, Gopi Kannan
There is an increasing trend of using polymeric materials in the vehicle interior compartment. While the polymers provide benefits in terms of flexibility in profiling, lighter weight and aesthetics but one of the challenges with the polymers is emission of volatile organic compounds (VOCs) during their usage and particularly at a temperature prevailing in the vehicle cabin. VOCs adversely impact the vehicle interior air quality and can pose a risk to occupants’ health. However, there is a lack of information on volatile organic compound (VOC) emissions from automotive interior materials. There are two types of methods, a whole vehicle chamber method (ISO 12219-1) and a bag method (ISO 12219-2) for evaluation of VOCs emissions from materials used in vehicle interior parts. ISO 12219-2 method describes quantitative testing of VOCs and semi-VOCs. This test method is quick and cost effective for analysis of materials for quick emission checks and can prove to be very effective in
PAtil, Yamini JitendraThipse, SukrutBawase, Moqtik
There is a scarcity of research in literature regarding the determination of Plenum Opening Area of cowl box. The area of the plenum opening in the cowl box significantly affects the airflow rate in fresh airflow modes, such as face and defrost modes, as well as issues related to water ingress. Primarily, the size of the plenum opening is determined by the necessary HVAC airflow rate. This study aims to investigate how the plenum opening area impacts both airflow discharge and the water ingress issue in the HVAC module. A novel approach is introduced in this research to determine the optimal plenum opening area of the cowl box, taking into account both airflow rate and water ingress concerns. The ANSYS FLUENT software is utilized to analyze airflow discharge in both face and defrost modes, while the SPH (Smooth Particle Hydrodynamics) based Preonlab tool is employed for water ingress analysis. Airflow discharge is evaluated for various plenum opening sizes in both modes, and the area
Baskar, SubramaniyanMahesh, AGopinathan, Nagarajan
Over the past few decades, Compressed Natural Gas (CNG) has gained popularity as an alternative fuel due to its lower operating cost compared to gasoline and diesel, for both passenger and commercial vehicles. In addition, it is considered more environmentally friendly and safer than traditional fossil fuels. Natural gas's density (0.7–0.9 kg/m3) is substantially less than that of gasoline (715–780 kg/m3) and diesel (849–959 kg/m3) at standard temperature and pressure. Consequently, CNG needs more storage space. To compensate for its low natural density, CNG is compressed and stored at high pressures (usually 200-250 bar) in on-board cylinders. This results in an effective fuel density of 180 kg/m3 at 200 bar and 215 kg/m3 at 250 bar. This compression allows more fuel to be stored, extending the vehicle's operating range per fill and minimising the need for refuelling. Natural Gas Vehicles (NGVs), particularly those in the commercial sector like buses and lorries, need numerous CNG
Choudhary, Aditya KantPetale, MahendraDutta, SurabhiBagul, Mithilesh
This research paper investigates the failure of an isolator clip used in the seat slider assembly, which guides and restricts the sliding motion of the tooth bracket within the seat. The component is made of C80 high-carbon spring steel, known for its high strength. According to the manufacturing process details, zinc plating was applied to the component for corrosion protection, as confirmed by EDS analysis. A fractographic examination of the failed part revealed a brittle, intergranular fracture morphology with visible cracks. Certain areas also exhibited micro-void coalescence, indicating a dimpled fracture surface. The primary failure mode was intergranular (IG) fracture. The delayed fracture was attributed to intergranular fracture mechanisms, micro-void coalescence, and the high strength of the steel, which made the component susceptible to hydrogen embrittlement. Hydrogen embrittlement occurs when hydrogen atoms become trapped along the grain boundaries, where they form hydrogen
Saindane, Mehul KishorBali, Shirish
Mounting strategies for vehicles with panoramic sunroofs remains a challenge owing to its high complexity to balance cost, performance and assembly efficiency. Achieving efficient and reliable headliner mounting solutions is one of the conundrums where cost optimization must go together with uncompromised performance. Traditional methods like Dual Lock Fasteners (DLFs), have set high benchmarks for robustness but at the cost of increased manufacturing complexity and expense . In pursuit of a more economical and production-friendly alternative, various plastic clip designs were explored. However, these solutions posed significant challenges during validation due to the stringent requirements for mounting feasibility, tolerance management, and long-term durability This paper introduces a novel hybrid plastic-metal clip solution that addresses those challenges comprehensively. [2] The new design achieves precise tolerance control, ensuring reliable headliner installation under varying
D, GowthamKumarasamy, Raj GaneshShoeb, MohdChauhan, Aarti
The application of AI/ML techniques to predict truck endgate bolt loosening represents a major innovation for the automotive industry, aligning with the principles of Industry 4.0. Traditional physical testing methods are both expensive and time-consuming, often identifying issues late in the development process and necessitating costly design changes and prototype builds. By harnessing AI/ML, manufacturers can now analyze endgate slam and bolt preload data to accurately forecast potential bolt loosening issues. This predictive capability not only enhances quality and safety standards but also significantly reduces the costs associated with tooling and builds. The AI/ML tool described in this paper can simulate a variety of load conditions and predict bolt loosening with over 90% accuracy, considering factors such as changes in loads, bolt diameters, washer sizes, and unexpected masses added to the endgate. It provides valuable design insights, such as recommending optimal bolt
Sivakrishna, MasaniDas, MahatSingh, AbhinavKarra, ManasaShienh, GurpreetLuebke, Amy
In autonomous vehicles, it is vital for the vehicle to drive in a manner that ensures the driver is comfortable and has confidence in the system, which ensures he does not feel compelled to intervene or take control of the vehicle. The system must consider environmental factors and other aspects to provide the driver with a comfortable and stress-free drive. In this regard, the road friction coefficient, which quantifies the grip experienced by the tire on a road, is a critical parameter to be considered by several comfort and safety functions. An inaccurate estimation of road friction coefficient can lead to discomfort in worst case safety risks for the driver, as the system would be over or underestimating the tire’s grip on the road and this alters the vehicle’s response to control inputs. In the context of Advanced Driver Assistance Systems (ADAS), dynamically estimating the road friction coefficient can significantly improve the safety and comfort of driving functions. However
Rangarajan, RishiSukumar Rajammal, Prem KumarSingh, Akshay PratapKumaravel, Sujeeth SelvamKop, AnandBharadwaj, Pavan
Improving transaxle efficiency is vital for enhancing the overall performance and energy economy of electric vehicles. This study presents a systematic approach to minimizing power losses in a single-speed, two-stage reduction e-transaxle (standalone) by implementing a series of component-level design optimizations. The investigation begins with the replacement of conventional transmission oil with a next-generation low-viscosity transmission fluid. By adopting a lower-viscosity lubricant, the internal fluid resistance is reduced, leading to lower churning losses and improved efficiency across a wide range of operating conditions. Following this, attention is directed toward refining the gear macro-geometry to create a gear set with reduced power losses. This involves adjustments to parameters such as module, helix angle, pressure angle, and tooth count, along with the introduction of a positive profile shift. These modifications improve the contact pattern, lower sliding friction, and
Agrawal, DeveshBhardwaj, AbhishekBhandari, Kiran Kamlakar
The present work demonstrates a transient Fluid-Structure-Interaction (FSI) based numerical methodology for estimation of aerodynamic-induced flutter of the rear bumper of a Sports Utility Vehicle (SUV). Finite Volume Method (FVM) based High-fidelity transient full vehicle aerodynamic simulations were conducted for the estimation of the transient aerodynamic load. Subsequently, by mapping this transient aero load onto the surface of the rear bumper, Finite Element Method (FEM) based dynamic structural simulations were performed to predict its response. The results obtained through simulations were then compared against experimental wind tunnel test data of a prototype car with modified bumper for the specific test-case. The pressure and the time series data of rear bumper deflection were captured at multiple probe locations from wind tunnel experiments at 140 and 200 kmph. The distribution of pressure on the rear surfaces of the car was well captured by the aerodynamic simulation at
Choudhury, SatyajitYenugu, SrinivasaWalia, RajatZander, DanielGullapalli, AtchyutBalan, ArunAstik, Pritesh
Air suction in a naturally aspirated engine is a crucial influencing parameter to dictate the specific fuel consumption and emissions. For a multi-cylinder engine, a turbocharger can well address this issue. However, due to the lack of availability of continuous exhaust energy pulses, in a single or two-cylinder engine, the usage of turbocharger is not recommended. A supercharger solution comes handy in this regard for a single or two-cylinder engine. In this exercise, we explore the possibility of the usage of a positive displacement type supercharger, to enhance the air flow rate of a single cylinder, naturally aspirated, diesel engine for genset application, operating at 1500 rpm. The supercharger parametric 3D CAD model has been prepared in Creo, with three design parameters i.e. (a) Generating radius, (b) depth of blower and (c) clearance between lobes & lobe and casing. The optimum roots blower design is expected to fulfil the target boost pressure, power consumption and
Satre, Santosh DadasahebMukherjee, NaliniRajput, SurendraNene, Devendra
This paper presents a comprehensive investigation into the mechanisms, risks, and mitigation strategies associated with thermal runaway in lithium-ion batteries used in electric vehicles (EVs). It begins by emphasizing the urgency of the issue, identifying key vulnerabilities within EV battery systems that contribute to runaway events. A multiscale, stage-wise breakdown of thermal runaway progression is provided, illustrating how physical, chemical, and thermal interactions compound during failure scenarios. The study analyzes global incident data from 2000 to 2025, revealing trends in human health impacts, vehicle damage, and public safety concerns. Particular attention is given to how battery aging, manufacturing defects, and external abuse conditions elevate the likelihood and severity of thermal runaway. Current emergency response protocols and state-of-the-art mitigation technologies are critically evaluated to identify best practices and existing gaps in safety management. A
Jain, GauravPremlal, PPathak, RahulGore, Pandurang
ISO/SAE 21434 emphasizes comprehensive cybersecurity risk management throughout the automotive lifecycle. However, specific guidance on validating cybersecurity measures at the production level remains limited. This paper addresses the gap in production-stage validation, particularly after End-of-Line (EOL) flashing, which includes configurations of security hardware and software protection (e.g., hardware register configuration, Debug and P-flash password settings etc.) Current automotive cybersecurity validation methods, despite adherence to ISO/SAE 21434, lack specific procedures for the production stage. The existing system-level validation using the ASPICE V-model (e.g., SWE.6, SYS.5) does not ensure the integrity and functionality of cybersecurity features in the final manufactured unit post-EOL flashing. This gap poses a risk of vulnerabilities being introduced during the EOL process, compromising critical security measures. To mitigate the cybersecurity risks in production
Chakraborty, SuchetaKulanthaisamy, NagarajanSankar, Ganesh
In agricultural tractors, braking actuation is usually done through control linkages consisting of a series of connected four-bar linkages with multiple pivots from the pedal to the brake pads. The quality of force transmission is critical as it directly affects the braking performance of the tractor. Forces measured at the end of the control linkage or brake pull rod often show deviation from theoretical values based on mechanical advantage calculations. This is due to various factors such as linkage transmission angle, elasticity, and friction losses in joints. A standardized simulation method needs to be developed and validated to predict the losses in the control linkage system. In this paper, the author proposes a simulation approach using multi-body dynamics, which includes contribution factors such as transmission angle, linkage elasticity, and friction in joints. MBS models for brake linkage systems for three different tractors were developed with flex bodies using ADAMS/View
Subbaiyan, Prasanna BalajiNizampatnam, BalaramakrishnaRedkar, DineshArun, GK, VinothR, SengottuPaulraj, Lemuel
The Mahindra XUV 3XO is a compact SUV, the first-generation of which was introduced in 2018. This paper explores some of the challenges entailed in developing the subsequent generation of this successful product, maintaining exterior design cues while at the same time improving its aerodynamic efficiency. A development approach is outlined that made use of both CFD simulation and Coastdown testing at MSPT (Mahindra SUV proving track). Drag coefficient improvement of 40 counts (1 count = 0.001 Cd) can be obtained for the best vehicle exterior configuration by paying particular attention to: AGS development to limit the drag due to cooling airflow into the engine compartment Front wheel deflector optimization Mid underbody cover development (beside the LH & RH side skirting) Wheel Rim optimization In this paper we have analyzed the impact of these design changes on the aerodynamic flow field, Pressure plots and consequently drag development over the vehicle length is highlighted. An
Vihan, Nikhil
There is rapidly increasing advancement in Connectivity, Autonomous, Subscription and Electrification features in vehicles which are being developed. These trends have resulted in an increase in attack surface and security risks on vehicles. To handle these growing risks, it has become important to include passive security systems such as Intrusion detection systems (IDS) which can detect successful or possible attempts of intrusion into vehicle systems compromising their security. In vehicles based on Zonal Architecture, two types of IDS can be implemented, Network based IDS (NIDS) and Host Based IDS (HIDS). The NIDS is implemented in Gateway Electronic Control Unit (ECU) and can monitor multiple networks connected to Gateway, whereas the HIDS usually monitors one single host ECU. Extensive research material is available on NIDS for CAN Networks. For example, the CAN Network in a vehicle is monitored for various abnormal behaviours such as increased busload and invalid signal values
E L, Nanda KumarMutagi, MeghaSonnad, PreetiSharma, Dhiraj
Ambient light reflecting off internal components of the car, specifically the Head-Up Display (HUD), creates unwanted reflections on the Windshield. These reflections can obscure the driver's field of view, potentially compromising safety and reducing visual comfort. The extent of this obscuration is influenced by geometrical factors such as the angle of the HUD and the curvature of the Windshield, which need to be analyzed and managed. The primary motivation is to improve driver safety and visual comfort. This is driven by the need to address the negative impact of ambient light reflecting off Head-Up Displays (HUDs), which can impair visibility through the Windshield. There is a need for tools and methods to address this issue proactively during the vehicle design phase. This study employs a tool-based modeling method to trace the pathways of ambient light from its source, reflecting off the HUD, and onto the Windshield using a dimensional modeling tool. It focuses on: Geometrical
Muchchandi, VinodAkula, Satya JayanthMahindrakar, PramodG S, Sharath
In today’s fast paced and competitive automotive market, meeting the customer’s expectation is the key to any OEM. This has led to development of downsized high performance engines with refinement as an important deliverable. However developing such high output engines do come with challenges of refinement, especially higher torsional vibrations leading to transmission noise issues. Hence, it becomes important to isolate the transmission system from these high torsional vibration input. To address this, one of the most common method is to adopt Dual Mass flywheel (DMF) as this component dampens torsional vibrations and isolates the transmission unit from the same. While Dual Mass Flywheel assemblies do great job in protecting the transmission units by not allowing the oscillations to pass through them, they do have their own natural resonance frequency band close to the engine idle (low) engine speeds, which must be avoided for a continuous operation otherwise it may lead to Dual Mass
Raiker, Rajanviswanatha, Hosur CJadhav, AashishJain, OjaseJadhav, Marisha