Your Destination for Mobility Engineering Resources

Announcements for SAE Mobilus

Browse All

Recent SAE Edge™ Research Reports

Browse All 177

Recent Books

Browse All 719

Recently Published

Browse All
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
Artificial Intelligence (AI) is radically transforming the automotive industry, particularly in the domain of passenger vehicles where personalization, safety, diagnostics, and efficiency. This paper presents an exploration of AI/ML applications through quadrant of the key pillars: Customer Experience (CX), Vehicle Diagnostics, Lifecycle Management, and Connected Technologies. Through detailed use cases, including AI-powered active suspension systems, intelligent fault code prioritization, and eco-routing strategies, we demonstrate how AI models such as machine learning, deep learning, and computer vision are reshaping both the user experience and engineering workflow of modern electric vehicles (EVs). This paper combines simulations, pseudo-algorithms and data-centric examples of the combined depth of functionality and deployment readiness of these technologies. In addition to technical effectiveness, the paper also discusses the challenges at field level in adopting AI at scale i.e
Hazra, SandipTangadpalliwar, SonaliKhan, Arkadip
The automotive regulatory landscape in India is evolving rapidly, driven by a dynamic policy intervention by GOI, striking push for sustainable mobility, safety, technological advancements, dEnvironmentally soundeeper localization, energy self-reliance, product quality control and simplified registration process. Key regulations cover areas like vehicle safety norms, emission norms, fuel economy norms, BIS QCO, the promotion of EVs and alternative fuel vehicles, R & D roadmaps, ELVs, incentive policies and vehicle registration reforms. India has been keeping a close eye on the automotive regulatory progress in the Europe as well as other developed countries as a cornerstone for technical harmonization, cross learning, gauge benefits and economic implications. India is progressively aligning its automotive regulations with global standards, particularly with UN Regulations and GTRs, while also considering unique Indian driving and environmental conditions. This alignment is crucial for
Patil, Dharmarayagouda
Predictive maintenance is critical to improving reliability, safety and operational efficiency of connected vehicles. However, classic supervised learning methods for fault prediction rely heavily on large-scale labeled data of failures, which are difficult to obtain and maintain a manually built dataset of failure events in real automotives settings. In this paper, we present a novel self-supervised anomaly detection model that makes predictions on the faults without the need for labeled failures by using only the operational data when the systems or robots are healthy. The method relies on self-supervised pretext tasks, like masked signal reconstruction and future telemetry prediction, to extract nominal multi-sensor dynamics (i.e., temperature, pressure, current, vibration) while jointly minimizing the deviation between encoded/decoded signals and normal patterns in the latent space. A unsupervised anomaly detection model is then used to detect when the learned patterns are violated
Kumar, PankajDeole, KaushikHivarkar, Umesh
Software Defined Vehicles (SDV), Software Defined Networks (SDN), Software Defined (Power) Grids (SDG) are just a few examples of how the Software Defined Transformation is unfolding across many industries today (collectively being referred to as Software Defined X – SDX). This paper defines a maturity model for Software Defined Transformation and evaluates different industries including Automotive on their evolution so far. This cross-industry view of SDX helps in analyzing where SDV’s could be headed. A 2020 paper [1] lays out the complexity of the automotive software, with companies pursuing several directions in this transformation. The automotive industry has not yet reached a consensus on the direction it is taking on SDV. While companies like Tesla are already making software centric cars, traditional OEMs like General Motors, Toyota, Ford etc. are making huge investments and redefining their business models, tech stacks and operations to leverage the power of software. There is
Mathur, Akshay RajMisra, AmitMakam, Sandeep
The integration of Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) has transformed various industries, offering substantial benefits. The application of these technologies in engine reliability testing has immense potential as they offer real-time monitoring and analysis of engine performance parameters. Engine reliability testing is vital for ensuring the safety, efficiency, and longevity of engines. Traditional methods are time consuming, expensive, and rely heavily on manual inspection and data analysis. This paper shows how IoT and ML technologies can enhance the efficiency of engine reliability testing. The paper includes the following case studies:
Yadav, Sanjay KumarKumar, PrabhakarR, DineshJoon, SushantRai, AyushTripathi, Vinay Mani
The automotive industry produces a vast amount of multilingual textual data ranging from technical manuals to diagnostic reports that demand efficient summarization and reliable semantic reasoning. At present, the traditional large language models (LLMs) operating at the token level struggle not only with cross-lingual understanding and domain-specific reasoning but also are prone to hallucinations, leading to inaccurate insights and responses [2, 5]. This paper introduces a Unified Concept Model (UCM) architecture for the automotive domain that processes language at the concept level using multilingual, modality-agnostic embeddings, enabling coherent cross-lingual summarization and reasoning. The UCM encodes entire sentences as semantic vectors by leveraging the SONAR embedding space, a multilingual, modality-agnostic sentence representation that supports over 200 languages. This approach to encoding facilitates a deeper understanding across language boundaries and complex technical
Singh, SamagraRavi, UtkarshVikram, PrateekShenoy, LakshmiAwasthi PhD, Anshuman
The modern vehicle is no longer a mechanical appliance—it has transformed into a software-defined cyber-physical system, integrating OTA updates, cloud-connected diagnostics, V2X services, and telematics-driven personalization. While this evolution promises unprecedented value in consumer experience and fleet operations, it also surfaces a dramatically expanded and evolving attack perimeter, especially across safety-critical ECUs and communication buses. Cyber vulnerabilities have shifted from isolated IT threats to real-time, embedded exploits. Controller area network (CAN), the backbone of vehicle bus systems, remains intrinsically insecure due to its lack of authentication and encryption, making it highly susceptible to message injection and denial-of-service by low-cost tools. Similarly, OEM implementations of BLE-based passive entry systems have proven vulnerable to replay and spoofing attacks with minimal hardware. In the Indian context, the transition to connected mobility is
Shah, RavindraAwasthi, Vibhu VaibhavKarle, Ujjwala
There is continuous push from the legislation for stringent fuel economy and emission regulations while the modern customers are demanding more engaging driving experience in terms of performance and refinement. To meet this Tata Motors has developed an advanced 1.2L 3-cylinder turbocharged gasoline direct injection engine. This next-generation powertrain delivers optimum efficiency, reduced emissions, superior performance with refined NVH characteristics. The key features used to enable these demanding requirements includes a 35 MPa fuel injection system, Miller Cycle operation and electrically actuated variable nozzel turbocharger (VNT). A uniquely designed BSVI complaint (WLTP ready) exhaust after-treatment system with Four-Way Conversion Catalyst (FWC+TM) ensures optimum emission control. A centrally mounted variable cam phaser minimizes pumping losses. The lightweight yet rigid all-aluminum engine structure, featuring an integrated structural oil sump, enhances durability and
Hosur, ViswanathaGhadge, Ganesh NarayanJoshi, ManojJadhav, AashishPanwar, Anupam
The transition to TREM V emission norms presents significant challenges for naturally aspirated (NA) off-highway engines. Off-highway applications like construction and agriculture segments require high load variability and extended duty cycles with increased BMEP resulting in high PM emissions, and increased exhaust temperatures with lower lambda levels. Given the cost-competitive nature of the segment, it also requires designing leaner intake and exhaust system. To overcome above mentioned challenges, holistic calibration strategies need to be adapted during development phase. To meet TREM V emission norms, solutions like advanced combustion, high-pressure fuel injection, EGR (exhaust gas recirculation), and optimized calibration had to be explored along with aftertreatment systems like Diesel Particulate Filters and Diesel oxidation catalysts. Implementation of aftertreatment systems for TREM V pre-dominantly with naturally aspirated engines will result in challenges associated to
Patil, Madhavi M.Ravukutam Sr, AnikethRaghu, M YMadhukar, Prahlad
A crash energy absorption technique and method improve the safety and structural integrity of electric vehicle battery packs during collisions, complying with global regulations. This analysis details an assembly featuring a battery housing for mounting battery cells, a crash member connected to the battery housing's periphery, and flexural members linked to the crash member. The flexural members are designed to absorb impact forces by deforming and storing potential energy during sudden impacts. This approach ensures energy is stored within the flexural elements and then transferred to the battery cells through progressive crushing. The design effectively delays intrusion, enhances battery safety, and minimizes cell-level damage. This solution improves occupant safety and prevents thermal runaway incidents while maintaining the battery's overall performance and reliability in EVs.
Amberkar S, SunilLakshman singh, MeenakumariBodaindala, Anil Kumar
This paper presents a comprehensive numerical methodology for simulating the coupled process-structure behavior of short glass fiber-reinforced, injection-molded thermoplastics. The approach integrates elastoplastic and anisotropic material characteristics using three engineering tools: Moldflow, Digimat, and ABAQUS. It accounts for fiber orientation and injection molding defects, linking to thermo-mechanical performance. This method enables accurate virtual modeling of real-time injection-molded components by transferring anisotropic data from Moldflow to ABAQUS. In this study, short fiber orientation and potential injection molding defects such as weld lines and residual stresses are discussed using Moldflow simulation. Besides, Digimat is employed as an interface tool to facilitate the transfer of Moldflow simulation results, namely fiber orientation and material behavior in the allied configurations directly into ABAQUS. This integration enables the evaluation of thermo-mechanical
T, KalingaYanamadala, Dharma TejaMattupalli, VenkataChirravuri, BhaskaraMiller, Ronald
Pedestrian safety is a critical concern in India, where rapid urbanization, increased vehicular traffic, and inadequate infrastructure pose significant risks to pedestrians. This study aims to analyze pedestrian accidents across various regions in India, drawing insights from comprehensive accident data. By examining accident patterns, risk factors, and contributing variables, we seek to inform policy recommendations and enhance pedestrian safety measures.
Howlader, AshimMehta, Pooja
Conventional ICE (internal Combustion Engine) tractors have single mechanical drivetrain used for propulsion of wheels, hydraulic and PTO drive and are designed to deliver power across range of operational zones leading to power wastage, reducing efficiency. This happens during Low Power Mode or low load operation. Extensive validation in Mahindra tractors reveal that such operations contribute to overall loss of 18–20%. Out of all factors, losses due to hydraulics is predominant and is close to 7–10 % of total power loss. In contrast, Hybrid tractors with Engine for propulsion of wheels alone and a dedicated Electric motor for PTO, Hydraulic functions. We have designed the system to offer enhanced operational flexibility through three distinct modes: Low Power Mode, Lift Assist Mode, and Implement Drive Mode. These modes ensure delivery of optimised performance while reducing the hydraulic losses & increased efficiency of the overall system. Low Power mode - powers essential vehicle
Natarajan, SaravananP, ShanmugavelJoshi, PriyankaSundaram, PavithraSameer, KamatSingh, RubyArvind, KumaranT, Senthil Kumar
Road accidents involving cut-in and sudden brake events on highways present major challenges to driver safety, often outpacing the response time of traditional Advanced Driver Assistance Systems (ADAS). The objective of this study is to predict potential collisions caused by cut-ins before ADAS intervention becomes necessary, allowing for earlier driver alerts and enhanced vehicle response. The proposed method employs machine learning and deep learning approaches, specifically Long Short-Term Memory (LSTM) networks, to forecast collision risks 0.5 to 3 seconds in advance. Synthetic data generation techniques are used to create rare but critical cut-in and braking scenarios, complementing real-world data from test vehicles and accident records. Key predictive features monitored include relative velocity, lateral velocity, and lane overlap, which provide dynamic indicators of imminent risk. Results show that the system achieves an average early warning time of 1.35 seconds in 40.206% of
Srivastava, RohanNayak, Apoorva S.Suvvari, Sai DileepSatwik, RahulBhattacharya, Abhinov
The distribution of mobility equipped with electrified power units is advancing towards carbon-neutral society. The electrified power units require an integration of numerous hardware components and large-scale software to optimize high-performance system. Additionally, a value-enhancement cycle of mobility needs to be accelerated more than ever. The challenge is to achieve high-quality performance and high-efficient development using Model-Based Development (MBD). The development process based on V-model has been applied to electrified power units in passenger vehicle. Traditionally, MBD has been primarily utilized in the left bank (performance design phase) of the V-model for power unit development. MBD in performance design phase has been widely implemented in research and development because it refines prototype performance and reduces the number of prototypes. However, applying the MBD to an entire power unit development process from performance design phase to performance
Ogata, KenichiroKatsuura, AkihiroTsuji, MinakoMatsumoto, TakumiIwase, HiromuNakasako, SeiyaTakahata, Motoki
The Government of India has mandated biofuel blending in automotive fuels to reduce crude oil imports and support the national economy. As part of this initiative, Oil Marketing Companies (OMCs) have begun nationwide blending of E20 fuel (20% ethanol in petrol). Ethanol supply is expected to exceed demand by the end of 2025 due to initiatives like the Pradhan Mantri JI-VAN Yojana. Alternative applications for ethanol are being explored; one promising approach is its use as a co-blend with diesel fuel (ED blends). However, ethanol’s low cetane number and poor lubricity pose challenges for direct use in diesel engines without modifications. ED blends demonstrated reduced emissions while maintaining performance comparable to conventional diesel. To further address concerns related to materials compatibility of ED blends with fuel system components, particularly plastomers that may impact engine durability, a detailed study was conducted using elastomers such as FVMQ, FKM, HNBR, and NBR in
Johnpeter, Justin PChakrahari, KiranChakradhar, MayaArora, AjayPrakash, ShantiPokhriyal, Naveen Kumar
Today, passenger car makers around the world are striving to meet the increasing demand for fuel economy, high performance, and silent engines. Corporate Average Fuel Economy (CAFE) regulations implemented in India to improve the fuel efficiency of a manufacturer's fleet of vehicles. CAFE goal is to reduce fuel consumption and, by extension, the emissions that contribute to climate change. CNG (Compressed Natural Gas) engines offer several advantages that help manufacturers meet and exceed these standards. The demand for CNG vehicles has surged exponentially in recent years, CNG engine better Fuel efficiency and advantage in CAFÉ norms make good case for OEM & Customer to use more CNG vehicle. CNG is dry fuel compared to gasoline. These dry fuels lack lubricating properties, unlike conventional fuels like petrol, diesel and biofuels, which are wet and liquid. Consequently, the operations and failures associated with these fuels differ. The materials and designs of engine parts, such as
Poonia, SanjayKumar, ChandanSharma, ShailenderKhan, PrasenjitBhat, AnoopP, PrasathNeb, Ashish
Noise quality at idle condition is an important factor which influences customer comfort. Modern diesel engines with stringent emission norms together with fuel economy requirements pose challenges to noise control. Common rail engine technology has advantage of precise fuel delivery and combustion control which needs optimization to achieve the conflicting requirements of noise, emission and fuel efficiency. Engine noise at low idle condition is dominated by combustion noise which depends on rate of pressure rise inside the cylinder during combustion. The important parameters which influence cylinder pressure rise are fuel injection timing, pilot injection quantity and its separation, rail pressure and EGR valve position. The study on effect of these parameters at varying levels demand large no of experiments. Taguchi design of experiments is a statistical technique which can be used to optimize these parameters by significantly reducing no of experiments needed to achieve the desired
P, PriyadarshanChavan, AmitA, KannanswamyPatil, SandeepChaudhari, Vishal V
The present disclosure is about combating Thermal runaway in Electric, Plug-in Hybrids and mild hybrid vehicles. This paper comprises of high-Voltage Battery pack containing Battery cells electrically coupled with Shape Memory Alloy along with Busbars. These connectors (Shape Memory Alloy) are programmed to operate in two states: First to electrically connect the cells with the busbars, second to disconnect the individual cells from electric connection beyond the threshold temperature. This mechanism enables the Battery cells to rapidly prevent the Battery from the Thermal runaway event which is caused from the cell level ensuring the Battery safety mechanically. Additionally, the Battery pack includes the cell monitoring system and Battery Monitoring System to enhance the above invention with regards to the safety of the vehicle. This configuration is implementable and retrofittable into existing battery systems, offering a robust solution to the challenges posed by prolonged vehicle
Reginald, RiniRout, SaswatVENKATESH, MuthukrishnanChauhan, Ashish JitendraSelvaraj, Elayanila
David Martin, CBMM Asia Bernardo Barile, CBMM Europe BV Caio Pisano, CBMM Europe BV Automotive high strength steels have specific microstructure-dependent forming characteristics. Global formability is generally associated with high uniform strain values which imply good drawability and stretch forming properties driven by pronounced work hardening. Local formability on the other hand is often measured by various fracture strain values—generally higher in single phase steels. In this respect, the so-called ‘local/global formability map’ concept has been established not only to provide a comprehensive methodology to characterize existing automotive steels but also to enable improvement strategies toward more balanced forming characteristics. Niobium (Nb) microalloying is a powerful tool to achieve both property improvement in general and property balance in particular. More than two decades of research has demonstrated that Nb-induced microstructural optimization is applicable to HSLA
Barile, Bernardo
Twist beam suspensions are widely utilised in passenger vehicles because of their simplicity and cost-efficiency, yet they provide engineers with a complex challenge as their performance depends entirely upon the structural properties of the beam itself. Traditional methodologies rely on the generation of Modal Neutral Files (MNF) based upon vehicle dynamics requirements and packaging constraints, which is a highly time-consuming process that starts failing to fulfil the demands of a market where development times are being exponentially reduced. Besides this, part of flexible body’s real behaviour might be lost in the process of converting multibody models into parametric ones, which, in turn, presents difficulties in modifying compliant-related items. Thanks to a novel approach followed jointly by Applus+ IDIADA & Mahindra, quick identification and optimisation of key tuneable items is achieved by employing a hybrid solution that combines full flexible and FE elements in Hexagon
Osorio, Alejandro GarcíaPrabhakara Rao, VageeshAsthana, ShivamRasal, Shraddhesh
The pursuit of sustainable transportation solutions requires continuous improvement in engine efficiency and performance. This study presents a comprehensive parametric analysis of high-horsepower diesel engine combustion modeling, focusing on fuel injector configurations to optimize power density and overall engine efficiency. The model was first validated with experimental data. Based on the validated model, a series of Design of Experiments (DoE) simulations were conducted, examining four distinct fuel injector hole configurations, each with four different spray inclusion angle (umbrella angle) variations. The set of different fuel injector configurations was selected through benchmarking analysis. The primary objective was to identify the most effective injector design for improved combustion characteristics and engine performance. Upon determining the superior configuration, further simulations were performed with increased injector through – flow to fine-tune the optimal design
Ailaboina, AkhilGandhi, NareshMarwaha, AksheyG, SuwarnaChogule, VijayBhat, Vishal
As urban population continues to grow, the safety of Vulnerable Road Users (VRUs) particularly in the presence of Heavy Good Vehicles (HGVs) has emerged as a critical concern. Research indicates that VRUs are at a 50% higher risk of fatal injury in collisions involving HGVs compared to passenger cars. To address this issue, this study proposes a novel pedestrian protection system that integrates LiDAR (Light Detection and Ranging) technology with a reusable airbag system to mitigate the severity of collisions. The proposed solution adopts a twofold approach for enhancing VRU protection in scenarios involving HGVs. In both approaches, LiDAR sensors are used to generate a real-time 3D model of the vehicle’s surroundings, enabling accurate VRU detection and predictive collision analysis. Scenario 1: When vehicle speed exceeds the first threshold and a collision is unavoidable, the onboard ECU activates front lid actuators, extending the vehicle's front lid which can be retracted back to
Patil, UdaySriharsha, ViswanathPillai, Rajiv