Browse Topic: Suspension systems

Items (3,667)
In order to improve the comfort performance in commercial vehicles, this study proposes a hierarchical control strategy that integrates the evaluation and migration of control algorithms. First, a quarter-vehicle model with four-degree-of-freedom (4-DOF) is constructed, incorporating the dynamics of the wheel, frame, driver’s cab, and seat. The key modal characteristics of the model are then verified through amplitude–frequency analysis, confirming their consistency with the typical vibration patterns observed in actual commercial vehicles, which provides the foundation for subsequent control strategy evaluation and migration. Then, based on a standard two-degree-of-freedom (2-DOF) suspension model, a weighted comprehensive evaluation function is developed to account for comfort, structural safety, handling stability, and both time- and frequency-domain performance indicators. Using this evaluation function, various control algorithms—including Skyhook control (SH), acceleration-based
Pan, TingPang, JianzhongWu, JinglaiZhang, JiuxiangKang, GongZhang, Yunqing
Tuned Mass Dampers (TMDs) are widely used in the automotive industry to mitigate Noise, Vibration, and Harshness (NVH) issues across various vehicle systems. These passive devices are particularly effective in reducing structural vibrations in components subjected to resonant excitation. However, real-world applications often face challenges due to manufacturing variability and system-level build differences, which can cause deviations in both the TMD’s tuned frequency (up to ±15%) and the vibration characteristics of the host structure. These uncertainties—in both the TMD properties and the vehicle subsystem dynamics—can be modeled using statistical distributions. This paper presents a generalized methodology for vibration analysis and design under uncertainty, combining reliability engineering with dynamic vibration modeling. The approach formulates a unified mathematical framework that incorporates probabilistic and stochastic modeling to assess TMD performance under a range of
Abbas, AhmadHaider, Syedd'Souza, Suneel
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving
Demiri, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
Passenger comfort is becoming the forefront of luxury private jets where noise needs to be kept to a minimum. One source of structure-borne noise is the vibration of the Passenger Service Unit (PSU) panel. These vibrations originate from the outer skin, excited by turbulent boundary layer, and are transmitted through the fuselage frame to the PSU panel. This panel resides overhead of passenger seating, it is composed of a corrugated honeycomb core sandwiched between thin face-sheets. This paper presents a systematic approach to improve the vibro-acoustic performance of a honeycomb core sandwich structure by employing core filler and facesheet patches. Topology Optimization (TO) is used to determine the optimal layouts of these design modifications. The vibro-acoustic performance of the PSU panel with facesheet patches and core filler is evaluated using a frequency response analysis in the commercial finite element solver OptiStruct. The effectiveness of vibration reduction will be
Russo, ConnorWhetstone, IsobelPatel, AnujWotten, ErikKim, Il Yong
This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while
Kim, HyosigSenkowski, AndresGona, KiranSaroha, LalitBoraiah, Mahesh
The tire model is a crucial component in the design of the K-characteristic of FSAE racing car suspensions, and directly influences the achievement of maximum cornering lateral force. Not only do the slip angle, vertical load, tire pressure, and camber angle affect the mechanical characteristics of the tire, but temperature is also an important influencing factor when FSAE vehicle tires operate at high speeds. However, the modeling process of traditional tire models based on temperature characteristics is often very complex. The FSAE tire test code (FSAE TTC) already has a large amount of official sample data, which provides a basis for data-driven neural network models. This study implemented a hybrid modeling methodology, constructing two cascaded feedforward neural networks that combine the physical interpretability of the Magic Formula tire model with the nonlinear approximation capabilities of neural networks. The first network model uses slip angle, vertical load, tire pressure
Liu, XiyuanWang, ShenyaoLi, MingyuanHuang, Jiayu
In recent years, premium vehicles have increasingly incorporated suspension systems capable of adjusting ride height. The primary function of these systems is to enable the vehicle to traverse uneven terrain by elevating the chassis, thereby preventing contact between the underbody and the road surface. Notably, air spring-based mechanisms enhance ride comfort by modulating the wheel rate. The system proposed in this study achieves ride height adjustment through vertical displacement of the spring’s lower seat. By constructing a detailed mechanical topology model using a dynamic simulation tool, this research aims to evaluate the feasibility of improving driving performance not only through height regulation but also by actively controlling the vehicle’s posture during motion.
Park, JaeyongSang Hoon, LeeJong Min, KimChoi, Jang Han
This paper presents a testing platform for the development of lateral stability control systems in independent motor electric vehicles (EVs). A 10 degree of freedom (DOF) vehicle simulation and a radio control test vehicle are constructed to enable controls validation scalable to full size vehicles. These vehicle simulations, or ‘digital twins’, have been widely adopted throughout the automotive industry due to their lower operating costs and ease of implementation. Virtual models are not perfect representations of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially true when testing safety-critical features such as stability control. As a result, a simulation environment working in conjunction with a test vehicle represents an optimal hybrid approach. In this work, a high fidelity vehicle model is constructed in the Matlab/Simulink environment. To capture the effect of suspension, the digital twin is capable of
Petersen, Nicholas ConnerRobinette, Darrell
This article deals with the development of a real-time capable, three-dimensional model of the Mercedes-Benz G-Class with flexible ladder frame that considers nonlinear suspension kinematics and force elements. The shift to new drivetrain technologies often results in a significant increase in vehicle weight and requires corresponding design modifications – also applying to off-road vehicles. These modifications result in changed stiffness of elements such as the ladder frame or anti-roll bar, which significantly affect vehicle dynamics and off-road performance. Therefore, strategic, efficient assessments must be made in early development stages, where no detailed information about individual systems and components is available yet, to detect and avoid potential massive, costly changes in later stages. This requires a “handmade” vehicle simulation model specifically tailored to this particular application, since the use of commercial multi-purpose simulation packages is not effective
Riebler, SandroPernsteiner, SamuelGranitz, ChristinaSchabauer, Martin
Vehicle pull under acceleration is a phenomenon commonly observed in high-performance vehicles and electric vehicles (EVs), primarily arising asymmetric driveshaft angles, drivetrain architecture, and suspension geometry. In addition to these mechanical factors, tire characteristics, particularly the tire lateral force generated at the contact patch, significantly influence this effect. The lateral force is intricately tied to the dynamics of the contact patch and the geometric design of the tire tread pattern. This study investigates the relationship between tread pattern geometry and vehicle pull under acceleration, emphasizing the role of tire lateral force variations. By employing finite element (FE) simulation, lateral force response variations (dfy/dfx) resulting from tread block deformation were analyzed. Based on these simulation, a robust analytical methodology for tread pattern evaluation and optimization was established. The developed tread pattern characteristic parameter
Yoon, YoungsamJang, DongjinKim, HyungjooLee, Jaekil
With the rapid development of automated driving and the increasing adoption of “zero-gravity” seats, the crash safety of highly reclined occupants has become a critical issue. The current THOR dummy, designed for frontal impacts in the standard upright posture, exhibits limitations when directly applied to reclined seating configurations, including insufficient spinal flexion capability and excessive posterior pelvic rotation. In this study, the thoracolumbar spine kinematics of the THUMS human body model, reconstructed against post-mortem human subject (PMHS) tests, were analyzed. A two-segment linear fitting was employed to characterize a “dummy-like” spinal flexion response, yielding a virtual rotational hinge located near the thoracolumbar joint of the original THOR model. The characteristic rotation angle obtained from THUMS showed a strong linear correlation with the flexion moment of the T12–L1 vertebrae. Based on this relationship, the rotational joint of the THOR dummy was
Guo, WenchengKuang, GaoyuanShen, WenxuanTan, PuyuanZhou, Qing
A suspension system was designed, fabricated, and tested following a systems design approach by an SAE Off-road Team from a North Midwest university. Compared to previous suspensions, the new suspension system is more reparable and contains a minimal number of custom parts, while still maintaining sufficient strength to withstand dynamic loads experienced when operating the vehicle. Modifications were also made to fit the newly designed vehicle body frame. As an integral part of the team’s 2025 Baja vehicle, the redesigned suspension system contributed to the vehicle’s improved performance during the 2025 SAE (Society of Automotive Engineers) Baja Competition. This paper presents a detailed account of the design, development, and fabrication process of the suspension system. The final design was tested and evaluated via both computer simulations and physical tests, whose efficiency and reliability were finally demonstrated by the team’s improved ranking in the 2025 Baja SAE Competition
Liu, YuchengAnderson, MatthewLarson, CodyRodgers, JoshuaSeberger, AaronLetcher, Todd
The performance of chassis suspension mechanisms critically affects vehicle handling, ride comfort, and safety. Implementing real-time health monitoring for chassis systems contributes to preventing severe consequences such as increased body roll or loss of handling stability caused by shock absorber softening or spring stiffness degradation under deteriorating operating conditions, while circumventing the substantial costs associated with professional facility-based chassis inspections. With the rapid development of sensing and data analytics technologies, data-driven approaches are increasingly used in health monitoring. This study aims to achieve online monitoring of chassis suspension performance degradation using a deep neural network (DNN). First, a half-car model incorporating both vertical and pitch motions was established to simulate bumpy road conditions, with the aim of constructing a dataset that includes key vehicle suspension parameters and vehicle states related to their
Liao, YinshengLei, YisongSu, AilinWang, ZhenfengShi, ShuaiZhang, LeiZhang, JunzhiMa, Changye
During the initial design phase, automotive Original Equipment Manufacturers (OEMs) require the adaptability to examine various suspension system architectures while maintaining focus on the specific performance objectives. Those requirements are expressed by Kinematics and Compliance (K&C) look-up tables and represent the footprint of what the suspension should look like in real-world applications. However, translating those requirements into the full geometric hardpoint layout is not straightforward. This process often relies on trial-and-error approaches, making it time consuming and requiring significant expertise. This challenge, known as ”target cascading,” remains a major hurdle for many engineers. The main objective of this paper is to cascade the suspension requirements from K&C look-up tables to hardpoint locations by adopting an automatic workflow and ensuring respect for constructive and feasibility constraints. Design space exploration was conducted using a robust
Brigida, PieroDi Carlo, PaoloDi Gioia, NiccolòGeluk, TheoTong, SonAlirand, MarcGorgoretti, DavideOcchineri, MarcoTassini, NicolaBerzi, Lorenzo
When a vehicle performs planar motion, the tire side force induces a jacking-up effect determined by the suspension roll center height governed by suspension geometry. These jacking forces also excite pitching motion. In this study, the pitching degree of freedom, along with roll degree of freedom, was incorporated in the bicycle model of the vehicle motion, hence it becomes four-degree-of-freedom model, and a new analytical method that applies modal analysis method to the model decomposes the motion of the sprung mass of the vehicle into mutually independent vibration modes. Since the superposition of these vibration modes can reproduce vehicle motion, these vibration modes are the fundamental factors governing sprung-mass behavior. Therefore, understanding how these vibration modes respond to design parameters provides a theoretical foundation to design desired vehicle dynamics from the early stage of car development. This report presents, by conducting modal analysis of the four
Kusaka, KaoruYuhara, TakahiroKoakutsu, Shingo
The main purpose of this study is to develop and validate an accurate calculation model for a hydraulic damper piston valve joint, enabling reliable torque specification and clamp behavior without full prototype iteration. Joint stiffness is a primary interest point. The joint features a bolted interface with a laminated shim stack of many thin disks with varying outer diameters. Analysis of such joints are uncommon in literature, making it challenging to quantify the effects of load distribution, truncation, and surface contact effects between members. The proposed models discussed in this paper are based on frustum load distribution combined with annular-plate bending and elastic-foundation effects to capture the effects of washer cupping. Concrete outputs of the calculator include member load distribution, bolt and member stiffnesses, torque-to-preload relationships, and an external-load simulation that predicts when individual members lose clamp load. Detailed internal hydraulic
Dresen, GabrielVollmar, RaceRoy Chowdhury, Sourav
Active suspension systems play a crucial role in improving vehicle ride comfort and handling stability. However, most existing studies focus on the low-frequency range below 20 Hz, leaving the suppression of high-frequency vibrations within 50–500 Hz largely unexplored, even though these vibrations strongly affect in-cabin noise and ride quality. To address this gap, this study introduces a quarter-car suspension model incorporating both bushing dynamics and a rigid-ring tire within a reinforcement learning (RL) framework. A major challenge for RL-based suspension control is its degradation in high-frequency performance. To overcome this issue, we design an innovative training framework that integrates multiple synergistic strategies. First, frequency-domain rewards are incorporated as auxiliary signals to explicitly guide policy optimization in the high-frequency band. Second, long short-term memory (LSTM) networks are embedded in both the Actor and Critic to capture the sequential
zhu, ZhehuiZhang, LijunMeng, DejianHu, Xingyu
Helical compression springs have been used widely in various industries from automotive, aerospace and construction to electronics and medical devices. In the automotive industry, they appear in many places such as suspension, valvetrain, etc., as well in the discharge check valve of Gasoline Direct Injection (GDI) pump, which is the subject of study due to a recent fracture in lab testing. A theoretical study is conducted first to establish the equation governing spring dynamic motion under impact velocity, which can be in high magnitude with surging shock wave along spring axis. A new spring shock wave equation is developed for spring axial motion coupled with coil torsional effect. This newly derived shock wave equation has a broader term than the classic spring formula found in most engineering books. In this paper, it shows that the classic spring shock wave equation is only a special case for the general wave equation newly discovered. Then, a theoretical formula on spring shock
Pang, Michael L.Gunturu, SrinuNorkin, Eugene
The transition to software-defined vehicles (SDVs) necessitates a paradigm shift in both control strategies and vehicle architecture. The EU-funded R&D project SmartCorners addresses this challenge by developing integrated, modular, and scalable smart corner systems (SCS) that combine in-wheel motor (IWM)-based propulsion, brake blending, active suspension system, and steer-by-wire functionality in one module. These SCS can be retrofit or smoothly integrated into the highly adaptable skateboard chassis architecture of modern electric vehicles (EVs), enabling scalable deployment across diverse vehicle types. The central approach of this paper is the utilization of artificial intelligence (AI) and machine learning (ML) to implement multi-layer, data-driven control strategies, facilitating real-time actuation, fault mitigation, and user-centric EV architecture. The SmartCorners project strives to demonstrate significant enhancements, including improved real-world driving range due to
Ratz, FlorianArmengaud, EricFormento, CeciliaMoscone, GiuliaSorrentino, GennaroBisciaio, GiorgioSorniotti, AldoAmati, NicolaBraun, DanielDeibler, BerndBoxberger, ValeriusSottile, SalvatoreIvanov, ValentinFuse, HiroyukiKompara, Tomaž
Parking assist systems are among the most widely adopted driver-assistance features in modern vehicles. A key component of these systems is the path planning module, which ensures accurate vehicle alignment within a parking slot while satisfying various constraints such as maintaining slot centering, avoiding collisions in confined spaces, minimizing maneuver count, and achieving the shortest feasible path. Multiple path generation techniques—such as geometric, polynomial-based, and search-based methods—have been developed to enable safe and efficient parking maneuvers. However, most of these approaches rely on the simplifying assumption that the vehicle’s instantaneous center of rotation (ICR) is fixed, typically located on the non-steering axle. In practice, the ICR is not constant and can vary significantly across vehicles due to several physical and kinematic factors, including steering geometry, tire slip characteristics, suspension configuration, and weight distribution
Awathe, ArpitPatanwala, AbizerJain, ArihantVarunjikar, Tejas
This research provides a unique contribution to the field of in-wheel motor drive electric vehicles (EVs) by addressing the challenges associated with the use of permanent magnet synchronous motors (PMSMs) for traction. These motors, integrated into the unsprung masses, increase the rotational inertia of the wheels, reducing ride smoothness on uneven roads. To mitigate this issue, we present an optimal Kalman filter for a magnetorheological (MR) control suspension system that correlates road inputs between the front and rear wheels. This filter significantly improves the estimation accuracy of state variables by incorporating the vertical motion of the motor, along with potential enhancements from wheelbase preview. To determine the most suitable coil spring types for use with MR dampers, we used the WDW-600 computer-controlled electronic universal testing machine to evaluate three coil spring types: constant pitch (model A), variable pitch (model B), and conical spring (model C). To
Gad, Ahmed ShehataDarakhshan Jabeen, SyedaEl-Zomor, Haytham M.Tolba, MohamedElamy, Mamdouh I.
Performing transportation and exploration tasks on rugged terrain requires both high load-bearing capacity and large suspension stroke. However, the corner module configurations applied to challenging terrain have rarely been explored. This article proposes an integrated framework that combines bionic principles with topology graph–based type synthesis. This framework leads to the creation of a reconfigurable wheel-legged mechanism capable of switching between wheeled locomotion and legged gait modes, which is then implemented as a corner module system. First, inspired by the skeletal–muscular system of the equine leg, a structure–function mapping relationship between the biological system and the mechanical system is established. Second, a multi-loop closed-chain mechanism with biomimetic morphology is represented in the form of graph theory. A configuration atlas of the wheel-legged hybrid mechanism is generated based on the contracted graph and open-loop kinematic chains, and
Gao, ZhenhaiZhang, HanyingChen, GuoyingZhang, SuminHan, Zongzhi
To address the rollover risk of six-axle semi-trailers due to their large mass, high center of gravity, and multi-axle articulation, a lateral force balance anti-rollover strategy based on the Ackermann steering principle is proposed. By establishing the wheel angle constraint equations for the full-wheel steering system of the six-axle semi-trailer, a rigid-body dynamic model considering the articulation characteristics is developed. The key control and observation parameters are included in the wheel angles, center of gravity lateral offset, yaw angular velocity, sideslip angle, and lateral load transfer rate. An SMC-PID joint controller is designed, in which the third axle steering angle of the tractor is optimized by the SMC controller, and the trailer’s three-axle steering angle tracking control is achieved by the PID controller. The nonlinear accumulation of centrifugal force and dynamic load transfer under high-speed emergency lane change conditions is suppressed by a
Zhang, QiyuanZhang, LeiLiao, ShengkunSun, JinxuHe, Jing
In the current scenario of EV revolution in the automotive industry, NVH performance of the vehicles is one of the major points of sale to the customers. Auxiliary components play one of the predominant roles in the contribution of noise to overall vehicle interior or exterior sound pressure levels, which impact customer vehicle comfort. CAE prediction of NVH performance of automotive components involves a lot of design iterative processes, large server space utilization, and time-consuming. To reduce cost and time, data-driven technologies like AI algorithms can help CAE engineers because of their high efficiency and high precision. In the current research, a wiper motor mount stiffness prediction algorithm was designed based on the historical data using CAE analysis and AI algorithms, and improved prediction accuracy by tuning the parameters of AI algorithms using grid search methodology. High prediction accuracy of wiper motor mount stiffness has been achieved with the method of
Paturi, Yuva Venkata Sekhar
This paper presents a novel sensitivity analysis framework for differential braking as a backup steering solution in fail-operational Steer-by-Wire systems. The fault-tolerant design approach of Steer-by-Wire and steering systems for highly automated driving relies on the availability of road wheel actuators (RWA). Redundancies are therefore commonly used to ensure fail-operationality. Since its widespread implementation in production vehicles through electronic stability control, the use of differential braking as a cost-effective measure is desirable to increase functional diversity. However, feasible lateral accelerations through this backup solution are limited compared to conventional steering systems and lie close to ordinary driving scenarios. To address this limitation, this work investigates the influence of chassis parameters on differential braking performance. After defining characteristic values and a simulation test plan, a preliminary analysis using a linear single-track
Salzwedel, LeonIatropoulos, JannesHeise, CedricFrohn, ChristianHenze, Roman
The present study details the design evolution and failure analysis of a novel hybrid stabilizer bar link (stab link) developed for the front suspension of a born electric sports utility vehicle (SUV) platform characterized by higher gross vehicle weight (GVW), increased wheel travel, and constrained packaging space. To address these challenges, a unique hybrid stab link was designed featuring dual plastic housings at both the metal ball joint ends, connected by a steel tube, and achieving a 30% weight reduction while offering enhanced articulation angles for extremely lower turning circle diameter (TCD) of the vehicle, compared to the conventional stab link. The unique hybrid stab failed under complex loading conditions during accelerated durability testing (ADT), prompting a comprehensive investigation. The failure analysis included road load data acquisition across various stab bar diameter configurations evolved during suspension tuning, different stabilizer link designs evolved
Selvendiran, PJ, RamkumarNayak, BhargavM, SudhanPatnala, Avinash
The spring link or the lower control arm (LCA) is a critical structural component in a multi-link rear suspension system especially in a sports utility vehicle (SUV). The design of the rear LCA is thus challenging due to higher loads owing to higher suspension articulation typical of a SUV and further complicated in a born electric vehicle (BEV) due to increased vehicle weight contributed by a large battery. In the present work, a novel LCA was designed for the rear suspension system of one such born electric SUV application. The unique link was designed to withstand 20% higher rear axle weight compared to the conventional LCA used in a typical SUV. The LCA housed the spring with increased stiffness and a semi-active damper with varying and higher damping forces which complicated the design. The link design was further complicated with stab link mounting provision and mass damper mounting for improved NVH performance. Furthermore, the link was designed to withstand significantly higher
Selvaraj, SaravananNayak, BhargavJ, RamkumarM, SudhanChaudhari, Varun
This research paper provides a comprehensive study on how Artificial Neural Networks (ANNs) can be deployed to predict the stiffness characteristics of a cantilever beam with a crack of various depths and positions. The most destructive source of failure is considered to be vibration, so the major focus of this paper will be on how the cracks affect the modal stiffness. This study has various applications, such as airplane wings, bridges, stadiums, and arenas. A common research gap was noticed amongst the existing studies; the position of the cracks in the cantilever wasn’t considered, but this paper discusses how the location of cracks severely affects the dynamic behaviour of the cantilever. This study was done by carrying out modal analysis on a cantilever of the same dimensions with different crack configurations. Various crack dimensions and orientations were analysed to understand the effects of the crack on the dynamic behaviour of the cantilever. From the modal analysis results
SB, HarshiniRajkumar, ManjariR, KrithikaK, AnushaK, DivyaBhaskara Rao, Lokavarapu
As there is a major shift in customer demand for energy efficient transportation, electric vehicle development has taken prominence worldwide as they provide pollution free and noise free mobility. The subframe being an important structural component of the chassis system, the designers always find it challenging to provide best-in-class rear subframe (RSF) optimized in terms of cost and weight within the available packaging space especially in an electric sport vehicular boundary. The main function of rear subframe is to transmit forces to BIW without deflections hence for this it should be very stiff. At the same time, it should be light in weight and simpler to industrialize. In the present work, the design evolution of a novel sub-frame assembly for a multilink rear suspension of a born electric sports utility vehicle (e-SUV) platform is detailed. With increased rear axle weight contributed by the battery weight and rear mounted motor, the design evolution of the rear subframe (RSF
Nidasosi, Basavraj MarutiJ, RamkumarNayak, BhargavMani, ArunM, Sudhan
The vibrating half-car model is used to represent the dynamic behavior of a truck’s dependent suspension system, capturing four degrees of freedom. This research investigates time and frequency responses of vibration behavior of half-car model with possible tire–road separation. This investigation is significant because all previously reported analyses based on the tire-road attachment were incorrect, particularly regarding the tire-road separation phenomenon. The differential equations are extended to enhance the accuracy of the model, incorporating tire–road separation conditions for both wheels. A numerical approach is applied to simulate the vertical and roll dynamics of the system under the separation assumption. The simulation results are validated through experiments conducted using ADAMS View software. Integrating the tire–road separation into the model results in dynamic responses that closely reflect real-world behavior. These findings provide valuable guidance for designing
Nguyen, Quy DangJazar, Reza
Speed bump detection through computer vision and deep learning is essential for advancing active suspension preview control and intelligent driving. Although substantial progress has been made in this field, there remains a need to enhance detection accuracy while reducing computational demands. This article introduces a novel single-stage speed bump detector, the Speed Bump Detector Based on You Only Look Once (SBD-YOLO), which utilizes the YOLOv9 architecture for speed bump identification. To better capture the deep global features of speed bumps, we propose an innovative convolutional module—specifically, a lightweight building block designed for efficient feature extraction—named the Aggregated-MBConv. Furthermore, we design a new YOLO backbone by stacking Mobile Inverted Bottleneck Convolution (MBConv) and Aggregated-MBConv modules, which reduces computational cost while enhancing detection accuracy. Additionally, we introduce a Squeeze-aggregated Excitation (SaE) attention
Mao, RuichiWu, JianWu, YukaiWang, HuiliangLi, JunWu, Guangqiang
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
High energy impact testing using free fall mass is a crucial method for evaluating the structural integrity, and safety performance of automotive components subjected to sudden impact forces. This study focuses on assessing critical parts such as wheel rims, suspension knuckles, commonly exposed to unintentional impacts during vehicle operation, maintenance, or collisions. The test involves dropping a standardized mass from predetermined heights onto the component to simulate real-world impact scenarios. Key performance indicators include deformation, crack propagation, fracture resistance, and energy absorption capacity. Wheel rims and knuckles are evaluated for their ability to maintain structural integrity under localized impact without compromising vehicle handling or safety. Seats and related interior structures are tested to ensure occupant protection during crash-like events. Other components, such as brackets, mounts, or housings, are included based on functional criticality
Roham, PrasadBagade, MohanSinnarkar, NitinPawar, Prashant RShinde, Vikram
Bogie suspension systems are becoming increasingly popular in tipper vehicles to enhance their performance and durability, especially in demanding environments like construction and mining areas [1]. Bolsters contribute significantly to the overall performance and durability of the bogie suspension systems of tipper vehicles by evenly distributing the loads across the whole suspension system. They act as shock absorbers and negate the impact caused by the rough terrains and heavy loads, thereby reducing stress on individual components and maintaining the structural integrity of the vehicle. Bolsters also help in improving the ride comfort and to maintain the position of the suspension system [2]. This study focuses on the comprehensive testing and evaluation of bolsters to understand their modes and displacement data derived from field data. The primary objective is to analyse the performance and behaviour of bolsters under various operational conditions. Critical manners of
V Dhage, YogeshKolage, Vikas
Automotive driveline design plays an important role in defining a vehicle’s Noise, Vibration and Harshness (NVH) characteristics. Driveline system, responsible for torque transfer from the engine/transmission to the wheels, is exposed to a wide spectrum of vibrational excitations. The industry’s shift toward turbocharged engines with fewer cylinders while maintaining the equivalent torque and power has led to increased low-frequency torsional vibrations. This paper presents some key design considerations to drive the NVH design of a driveline system using linear dynamic FE simulations. Using an E-W All-Wheel Drive driveline architecture with independent suspension as a case study, the influence of various subsystem modes on driveline NVH performance is examined. The paper further explores the strategies for vibration isolation, motion control, and mode management to identify the optimal bushing rates and its location. Furthermore, it examines the ideal bushing specifications for
Joshi, Atul KamalakarraoSubramanian, MANOJ
Nowadays, customers expect excellent cabin insulation and superior ride comfort in electric vehicles. OEMs focus on fine tuning the suspension system in electric vehicle to isolate the road induced shocks which finally offers superior ride quality. This paper focuses on enhancing the ride comfort by reducing the road excitation which originates mainly due to road inputs. Higher steering wheel vibration is perceived on the test vehicle on rough road surfaces. To determine the predominant force transfer path, Multi reference Transfer Path Analysis (MTPA) is performed on the front and rear suspension. Based on the finding from MTPA, various recommendations are explored and the effect of each modification is discussed. Apart from this, Operational Deflection Shape (ODS) analysis is used to determine the deflection shape on the entire steering system . Based on ODS findings, recommendations like dynamic stiffness improvements on the steering column and steering wheel are explored and the
S, Nataraja MoorthyRao, ManchiSelvam, EbinezerRaghavendran, Prasath
The handling of a vehicle is crucial to the perception of its dynamic characteristics, such as comfort, stability, composure, sportiness, and precision. Kinematics and Elasto-kinematics, also known as Kinematics and Compliance (K&C), form the basis of an automobile's handling characteristics. Kinematics focuses on the movement of suspension components, including wheels, axles, and linkages, and how these movements relate to the vehicle's body motion. Compliance refers to the suspension's ability to deform under load, primarily due to the flexibility of springs, bushings, and other elastic components. Elastomer bushings, as flexible elements in the kinematic chain, significantly impact K&C and require a detailed study. Suspension bush stiffness is typically measured through static and dynamic tests, in various directions – radial, axial, torsional, etc. Tests involve applying a force or torque and measuring the resulting deflection and/or rotation. These measurements are used to
Avhad, Anish
Fatigue analysis is a vital aspect of suspension design, especially for load bearing components such as the Rear Twist Beam, where durability under cyclic loading is essential for long-term vehicle performance. Among the various durability tests, the roll fatigue test is a key procedure for validating suspension strength and reliability. However, conducting physical roll fatigue tests can be both expensive and time consuming, particularly when multiple design iterations are required. This not only increases cost but also extends the development timeline. This study presents a virtual simulation methodology that replicates roll fatigue test conditions within a finite element analysis environment, enabling early fatigue assessment and design optimization. Developed to support the early design phase, the roll fatigue test simulation process ensures robust designs that meet targeted fatigue life requirements. The approach begins with a detailed understanding of the physical roll fatigue
Kokare, SanjayNagapurkar, TejasIqbal, Shoaib
In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing. This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high
Goli, Naga Aswani KumarPrasad, Tej Pratap
This paper focuses on the development of a lightweight, functionally integrated Front-End Structure (FES) using plastic-metal hybrid injection molding technology. The objective is to achieve modularization, part consolidation, weight and cost reduction. The proposed design integrates multiple components into a single module which makes assembly faster and easier. A mounting strategy with fixation features was added into the structure, which effectively supports various components and sub-assemblies. Component-level Finite Element Analysis (FEA) was carried out which includes static strength analysis, bending and torsional stiffness analysis, modal analysis as well as latch pull test to achieve required structural strength. Ribbing structures were designed and optimized based on FEA result to provide the necessary strength and stiffness to the structure within the minimum weight. Moldflow analysis was carried out to evaluate manufacturability with focusing on gate design, minimizing
Srivastava, SanjayThakoor, Shruti GhanshyamSonkusare, Shailesh
In the evolving landscape of the automotive industry, enhancing passenger comfort and ride quality has become a key differentiator for manufacturers. While suspension systems have traditionally received significant attention, powertrain isolation through engine mounts plays an equally critical role in controlling noise, vibration, and harshness (NVH). Engine mounts are not only responsible for supporting the powertrain’s weight but also for mitigating the transmission of unbalanced engine forces to the vehicle body. Modern engine mount designs aim to eliminate any metal-to-metal contact between the powertrain and chassis, thereby achieving optimal vibration isolation. This study proposes a refined approach to completely decouple the powertrain from the vehicle structure, ensuring minimal vibration transfer and thereby extending the operational life and performance of the engine mount system.
Hazra, SandipNaik, Sarang PramodMore, Vishwas
Designing and manufacturing a support ring (POM ring -Polyoxymethylene ring) for a MacPherson strut suspension system brings unique set of challenges due to the high-performance and durability demands for Indian road application. Support ring along with the jounce bumper used in the shock absorber is designed to absorb the strong shock coming from the road inputs when suspension travel reached to the maximum limit. thereby absorbing the impact energy and preventing it from transferring it to the body. A bump stopper for a suspension of a vehicle is made of poly urethane (PU) material and is surrounded by a support ring or POM ring made up of Polyoxymethylene material. The bump stopper deflects into bellow shape during the absorption of impact energy. In the present paper, the authors have demonstrated the key challenges experienced in successfully designing the support ring post initial failure experienced in the validation phase which was unprecedented. The authors detail the failure
Koritala, Ashok KumarMalekar, AmitKulkarni, PurushottamS, SivashankarMishra, HarshitGanesh, Mohan SelvakumarPatnala, AvinashJ, RamkumarNayak, BhargavM, Sudhan
This study focuses on the effect of door seal compression prediction and its impact on structure borne NVH in trucks. Customer perception of vibrations are envisaged as quality criteria. It is necessary to determine the contribution of seal stiffness due to seal compression under closed condition of the door rather than considering stiffness of the door seal under uncompressed conditions. The dynamic stiffness of door seal is determined from analysis of non-linear type. The simulations are built using the Mooney - Rivlin model. The parameters influencing the compression of door seals in both two – dimension and three – dimension, are identified from the analysis. This involves contemplating the appropriate seal mounted boundary condition on the body and the door of the vehicle. The stiffness after compression of seal is extracted from this non-linear analysis which is further used to obtain the vibration modes for the doors in the truck cabin. As a part of next step, the compressed
L, KavyaRamanathan, Vijay
This paper focuses on the cabin sound quality refinement and the tactile vibration reduction during horn application in the electric vehicle. A loud cracking sound inside the cabin and higher accelerator pedal vibration are perceived while operating the horn. Sound diagnosis is carried out to find out the frequencies causing the cracking noise. Transfer path analysis is conducted to identify the nature of noise and the predominant path through which forces transfer. Based on finding from TPA, various recommendations are evaluated which reduced the noise to a certain extent. Operational Deflection Shape (ODS) is conducted on the horn mounting bracket and on the body to identify the component having higher deflection at the identified frequencies. Recommendations like DPDS improvement on the horn bracket and the body is assessed and the effect of each outcome is discussed. With all the recommendations proposed, the cabin noise levels are reduced by ~ 8 dB (A) and the accelerator pedal
S, Nataraja MoorthyRao, ManchiR, Ashwin sathyaS, THARAKESWARULURaghavendran, Prasath
The automotive industry is rapidly evolving with technologies such as vehicle electrification, autonomous driving, Advanced Driver Assistance Systems (ADAS), and active suspension systems. Testing and validating these technologies under India’s diverse and complex road conditions is a major challenge. Physical testing alone is often impractical due to variability in road surfaces, traffic patterns, and environmental conditions, as well as safety constraints. Virtual testing using high-fidelity digital twins of road corridors offers an effective solution for replicating real-world conditions in a controlled environment. This paper highlights the representation of Indian road corridors as digital twins in ASAM OpenDRIVE and OpenCRG formats, emphasizing the critical elements required for realistic simulation of vehicle, tire, and ADAS performance. The digital twin incorporates detailed 3D road profiles (X-Y-Z coordinates), capturing the geometry and surface variations of Indian roads. The
Joshi, Omkar PrakashShinde, VikramPawar, Prashant R
This work focuses on the prediction of Trimmed Body Noise Transfer Function (NTF) using Glazed BIW (body in white) structural model characteristics by leveraging Machine Learning (ML) technique. Inputs such as Glazed BIW (GBIW) attachment dynamic stiffness, Body Panel Vibration Transfer Functions (VTF) and Driver Ear level NTFs are employed to predict Trimmed Body NTF for a particular hard point. An iterative process of performing design modifications on the BIW to verify its effect on BIW performance and therefore on Trimmed body NTF is undertaken. BIW geometric parameters are varied in an organized manner to generate hundreds of data points at GBIW level which are provided as input to the train the ML model to predict the trimmed body level NTF. The outcome provides crucial insights of how the trimmed body NTF is closely related to the GBIW design characteristics. This ML approach of predicting trimmed body NTF based on GBIW characteristics provides critical insight about GBIW design
Kulkarni, Prasad RameshBijwe, VilasKulkarni, ShirishSahu, DilipInamdar, Pushpak
The increasing adoption of electric vehicles (EVs) has intensified the demand for advanced elastomeric materials capable of meeting stringent noise, vibration and harshness (NVH) requirements. Unlike internal combustion engine (ICE) vehicles, EVs lack traditional masking noise generated by the powertrain. In the automotive industry, the dynamic stiffness of elastomers in internal combustion engines has traditionally been determined using hydraulic test rigs, with test frequencies limited to a maximum of 1,000 Hz. Measurements above this frequency range have not been possible and are conducted only through computerized FE or CAE calculation models. Electric drive systems, however, generate distinct tonal noise components in the high-frequency range up to 10,000 Hz, which are clearly perceptible even at low sound pressure levels. Consequently, the dynamic stiffness characteristics of elastomers up to 3,000 Hz are critical for optimizing NVH performance in EVs. This study focuses on high
Bohne, ChristianGröne, Michael
Higher road noise is perceived in the cabin when the test vehicle encounters road irregularities like bump or pothole in the public roads. The transfer of transient road inputs inside the body caused objectionable cabin noise. Measurements are conducted at different road surfaces to identify the patch where the objective data well correlated with the noise measured at the public road. Wavelet analysis is carried out to identify the frequency zones since the events are transient in nature. TPA is carried out in time domain to identify the nature of the noise and the dominant path through which the transient road forces are transferring inside the body. Based on the outcome of TPA, various countermeasures like reduction of dynamic stiffness of suspension bushes, TMDs on the path are proposed to reduce the structure borne noise. Criteria which need to be considered for reduction of cabin noise due to transient road inputs is also discussed.
S, Nataraja MoorthyRao, ManchiSelvam, EbinezerRaghavendran, Prasath
Generally, in an electric sports utility vehicle with rear mounted powertrain the mass distribution is greater in the rear compared to front. This higher rear to front weight distribution results in oversteer behavior during high-speed cornering deteriorating vehicle handling & risking passenger safety. To compensate this inherent oversteer nature of such vehicles & produce understeer behavior, the steering rack is placed frontwards of the front wheel center for toe-out behavior due to lateral compliance during cornering. This compensation measure results in lower Ackermann percentage resulting in higher turning circle diameter deteriorating vehicle maneuverability. This paper proposes a design to obtain ideal understeer gradient with minimal turning circle diameter through utilization of split link technology with a McPherson Strut based suspension framework & frontwards placed steering rack. This suspension is utilized in our Mahindra Inglo platform. This paper elaborates on how
Nadkarni, Ameya RavindraMhatre, NitijPatnala, AvinashNAYAK, Bhargav
Items per page:
1 – 50 of 3667