Sealed electronic components are the basic components of aerospace equipment, but the issue of internal loose particles greatly increases the risk of aerospace equipment. Traditional material recognition technology has a low recognition rate and is difficult to be applied in practice. To address this issue, this article proposes transforming the problem of acquiring material information into the multi-category recognition problem. First, constructing an experimental platform for material recognition. Features for material identification are selected and extracted from the signals, forming a feature vector, and ultimately establishing material datasets. Then, the problem of material data imbalance is addressed through a newly designed direct artificial sample generation method. Finally, various identification algorithms are compared, and the optimal material identification model is integrated into the system for practical testing. The results show that the proposed material

Gao, Yajie, Wang, Guotao, Jiang, Aiping, Yan, Huizhen

Design of a Permanent Magnet Biased Radial Magnetic Bearing for Energy Storage of Vehicle Flywheels

2023-01-702110/30/2023

In order to exert the maximum capability of flywheel energy storage system( FESS), a permanent magnet biased radial magnetic bearing (PMRB) was designed for the FESS. In this paper the authors walk systematically through design and verification of the PMRB. Sections 1 and 2 introduce the working principles and mathematical models. Sections 3 and 4 details design and simulation process. In section 5, a comparison of the current stiffness and displacement stiffness are made between analysis and measurements. Finally, a brief summary and forecast was made.

Jing, Li, Yang, Binglin, Sha, Yingdi

Recurrent Neural Network Model for On-Board Estimation of the Side-Slip Angle in a Four-Wheel Drive and Steering Vehicle

15-17-01-0003

09/23/2023

Abstract A valuable quantity for analyzing the lateral dynamics of road vehicles is the side-slip angle, that is, the angle between the vehicle’s longitudinal axis and its speed direction. A reliable real-time side-slip angle value enables several features, such as stability controls, identification of understeer and oversteer conditions, estimation of lateral forces during cornering, or tire grip and wear estimation. Since the direct measurement of this variable can only be done with complex and expensive devices, it is worth trying to estimate it through virtual sensors based on mathematical models. This article illustrates a methodology for real-time on-board estimation of the side-slip angle through a machine learning model (SSE—side-slip estimator). It exploits a recurrent neural network trained and tested via on-road experimental data acquisition. In particular, the machine learning model only uses input signals from a standard road car sensor configuration. The model

Giuliacci, Tiziano Alberto, Ballesio, Stefano, Fainello, Marco, Mair, Ulrich, King, Julian

Recurrent Neural Network Model for On-Board Estimation of the Side-Slip Angle in a Four-Wheel Drive and Steering Vehicle

15-17-01-0003-TEST-REC09/23/2023

Giuliacci, Tiziano Alberto, Ballesio, Stefano, Fainello, Marco, Mair, Ulrich, King, Julian

Applications of Neural Networks to Metallic Flexor Geometry Optimization of Flat Wipers

15-17-01-0002

09/09/2023

Abstract In recent years, demands of flat wipers have rapidly increased in the vehicle industry due to their simpler structure compared to the conventional wipers. Procedures for evaluating the appropriate metallic flexor geometry, which is one of the major components of the flat wiper, were proposed in the authors’ previous study. However, the computational cost of the aforementioned procedures seems to be unaffordable to the industry. The discrete Winkler model regarding the flexor as the Euler–Bernoulli beam is established as the mathematical model in this study to simulate a flexor compressed against a surface at various wiping angles. The deflection of the beam is solved using a finite difference method, and the calculated contact pressure distributions agree fairly with those based on the corresponding finite element model. Flexor designs are paired with various windshield surfaces to accumulate a sufficiently large simulation database based on the mathematical model. An

Chu, Yi-Tzu, Huang, Ting-Chuan, Liao, Kuo-Chi

Backend-based State-of-Charge Control as an Operating Strategy for a Serial PHEV

2023-01-120106/26/2023

In previous work, a serial hybrid powertrain concept with a phlegmatised ICE has been described. Drivability is to be ensured through an innovative predictive operating strategy. Battery State-of-Charge (SoC) is controlled using a backend-based prediction of energy consumption on a given route based on road map and traffic data. In this paper, a spotlight is thrown on the proposed control architecture. On the top level of the controller, a Dynamic Programming algorithm finds an optimal reference trajectory for the SoC over a known route with the goal of avoiding certain Worst-Case scenarios commonly associated with the serial hybrid powertrain topology. Close adherence to the reference trajectory is ensured on a lower level through Model Predictive Control, taking into account additional factors such as battery stress. These control layers closely represent the map data distributed on the on-board bus network of state-of-the-art road vehicles under the current ADASIS standard. The

Böhme, Maximilian, Gerdts, Matthias, Trapp, Christian

Recognition Method for Electronic Component Signals Based on LR-SMOTE and Improved Random Forest Algorithm

01-17-01-0005

06/10/2023

Loose particles are a major problem affecting the performance and safety of aerospace electronic components. The current particle impact noise detection (PIND) method used in these components suffers from two main issues: data collection imbalance and unstable machine-learning-based recognition models that lead to redundant signal misclassification and reduced detection accuracy. To address these issues, we propose a signal identification method using the limited random synthetic minority oversampling technique (LR-SMOTE) for unbalanced data processing and an optimized random forest (RF) algorithm to detect loose particles. LR-SMOTE expands the generation space beyond the original SMOTE oversampling algorithm, generating more representative data for underrepresented classes. We then use an RF optimization algorithm based on the correlation measure to identify loose particle signals in balanced data. Our experimental results demonstrate that the LR-SMOTE algorithm has a better data

Lv, Bingze, Wang, Guotao, Li, Shuo, Wang, Shicheng, Liang, Xiaowen

Experimental Investigation on Genetic Algorithm optimized Proportional Integral Derivative Based Active Suspension System

2025-01-001405/05/2023

In this work, Genetic Algorithm (GA) optimized Proportional Integral Derivative (PID) controller is employed. The PID gain values are optimally tuned based on the objective function formulated using the Integral Time Absolute Error (ITAE) criteria of various suspension measures like vehicle body displacement, suspension and tire deflections. The proposed GAPID controller is experimentally validated through the 3-DOF quarter-car test rig model. The fabricated model with passive suspension system (PASS) and active suspension system (ACSS) provided with an electrical actuator as base excitation is pictured. The schematic representation of the fabricated test set-up with and without ACSS is also illustrated. Further, simulation and experimental response of the fabricated model with and without ACSS are compared. It is identified that the proposed GAPID controller attenuates the sprung mass acceleration by about 41.64 % and 29.13 % compared with PASS for the theoretical as well as

A, Arivazhagan

Characterize the Sound Field Generated from a Vehicle Horn by Pellicular Analysis

2025-01-005805/05/2023

To predict the sound field produced by a vehicle horn requires a good source representation of it in the full vehicle model. This paper investigates the characterization of a physical vehicle horn by an inverse method called pellicular analysis. To implement this method, firstly an acoustic testing is performed to measure the sound pressure radiated from the horn at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual horn, the locations of each microphone and measured sound pressure data, pellicular analysis is adopted to recover a set of vibration pattern of the virtual horn. The virtual horn and the recovered vibration information are then incorporated in a full vehicle numerical model to simulate its exterior sound field. The validity of this approach is confirmed by comparing the prediction for a horn in a production vehicle to the corresponding physical test which is required to meet the Brazilian regulation CONTRAN 764/2018.

Yang, Wenlong, MELO, ANDRE

Development of Offline Simulation Software for Active Sound Design in Electric Vehicles

2025-01-001705/05/2023

With the increasing adoption of electric vehicles (EVs), Active Sound Design (ASD) has emerged as a crucial method to enhance both the sound quality and driving experience, addressing the lack of distinctive engine sounds present in internal combustion vehicles. This paper presents an ASD offline simulation software developed on the MATLAB platform to address these challenges. The software integrates a vehicle dynamics model with three key sound synthesis algorithms: order synthesis, pitch shifting, and granular synthesis, allowing for comprehensive control strategy development, real-time sound playback, and rapid adjustment. The software consists of several functional modules, including configuration, order generator, pitch shifting, and granular synthesis interfaces, which support user-friendly operation and flexible sound parameter adjustments. Users can simulate different driving conditions and evaluate the acoustic performance of the ASD system in real time. The system also allows

Qian, Yushu, Liu, Zhien, xiong, chenggang

A study on active sound design and control method for vehicle interior hybrid noise to enhance sound quality

2025-01-001105/05/2023

With the current popularity of new energy vehicles and the continuous development of intelligent cabin technology, the demand for acoustic comfort within automotive cockpit is increasing. A multi-channel feedforward active sound design and control method was proposed to improve the sound quality of the hybrid broadband and narrowband noise inside the test vehicle. The method selectively designed the target amplitudes for broadband noise and narrowband noise in the vehicle to satisfy passengers comfort, mainly including the sound design phase and the control phase. During the sound design phase, objective sound quality parameter analysis was first conducted on the noise of the prototype vehicle, followed by an evaluation of the sound quality with semantic differential method. An active acoustic design strategy focusing on comfort, motivation sense and annoyance perception were proposed, including a formula for the target amplitude of adjustment order and sound pressure level. The sound

Liu, Xuexian, Xu, Wenxuan

Evaluation of Material Damping Ratio of Electronic Ignition Switch Module to Enhance its Finite Element Model Physics for Harmonic Response

2025-01-010905/05/2023

The present paper investigates the material damping ratio parameter in detailed manner for different Electronic Ignition Switch Module (EISM) utilized in two-wheeler automobiles. At first, investigation is carried out for developing a Finite Element Method (FEM) based simulation model. The simulation is performed by matching the failure areas of critical component in assembly with physical sinusoidal vibration based shaker table test results (particularly breakage) by utilizing different damping ratios for the assembly. The damping ratio parameter is further utilized to perform FEM based harmonic response analysis for different EISM and evaluate critical structural breakage zones. The breakage zones predicted by simulation were found to be aligned with breakage zones shown by shaker table test results. The results are validated, specifically considering the damping ratio parameter. The FEM based harmonic response analysis is performed for a particular acceleration excitation in between

Shah, Viren, Kalurkar, Shantanu, Kushari, Subrata, KUMAR, Rahul, Miraje, Jitendra, D, Suresh, Parandkar, Parag

Navigating Evolving Vehicle NVH Challenges with Application of Emerging Technologies in Artificial Intelligence and Machine Learning

2025-01-013005/05/2023

The multifaceted, fast-paced evolution in the automotive industry includes noise and vibration (NVH) behavior of products for regulatory requirements and ever-increasing customer preferences and expectations for comfort. There is pressing need for automotive engineers to explore new and advanced technologies to achieve a ‘First Time Right’ product development approach for NVH design and deliver high-quality products in shorter timeframes. Artificial Intelligence (AI) and Machine Learning (ML) are trending transformative technologies reshaping numerous industries. AI enables machines to replicate human cognitive functions, such as reasoning and decision-making, while ML, a branch of AI, employs algorithms that allow systems to learn and improve from data over time. The purpose of the paper is to show an approach of using machine learning techniques to analyze the impact of variations in structural design parameters on vehicle NVH responses. The study begins by executing the Design of

Miskin, Atul R., Parmar, Azan, Raj, Sonia, himakuntla, Uma Maheswar

Data-Driven Machine Learning Approach for Rattle Risk Mitigation

2025-01-012605/05/2023

In the modern automotive industry, squeak and rattle issues are critical factors affecting vehicle perceived quality and customer satisfaction. Traditional approaches to predicting and mitigating these problems heavily rely on physical testing and simulation technologies, which can be time-consuming and resource-intensive, especially for larger models. In this study, we propose a data-driven machine learning approach to mitigate rattle risks more efficiently. In this study, a floor console model has been evaluated using the traditional simulation-based E-line method to pinpoint high-risk areas. Data generation is performed by varying material properties, thickness, and flexible connection stiffness using the Modified Extensible Lattice Sequence (MELS) sampling algorithm, creating a diverse and comprehensive dataset for generating a machine learning (ML) model. Utilizing the dataset, the top contributing variables were identified for training the ML models. Various machine-learning

Parmar, Azan, Rao, Sohan, Reddy, Hari Krishna

Development of a Detailed 3D Finite Element Model for a Lithium-Ion Battery Subject to Abuse Loading

2023-01-000704/11/2023

Lithium-ion batteries (LIBs) have been used as the main power source for Electric vehicles (EVs) in recent years. The mechanical behavior of LIBs subject to crush loading is crucial in assessing and improving the impact safety of battery systems and EVs. In this work, a detailed 3D finite element model for a commercial vehicle battery was built, in order to better understand battery failure behavior under various loading conditions. The model included the major components of a prismatic battery jellyroll, i.e., cathodes, anodes, and separators. The models for these components were validated against the corresponding material coupon tests (e.g., tension and compression). Then the components were integrated into the cell level model for simulation of jellyroll loading and damage behavior under three types of compressive indenter loading: (1) Flat-end punch, (2) Hemispherical punch and (3) Round-edge wedge. The comparisons showed reasonable agreement between modeling and experiments. With

Development of a Detailed 3D Finite Element Model for a Lithium-Ion Battery Subject to Abuse Loading

2023-01-0007-TEST-REC04/11/2023

electric - take 2

SAE-PP-0779211/04/2022

electric

SintzADMIn, Jeneane

Effect of anti-dive suspension geometry on braking stability

2022-01-117209/19/2022

Suspension plays a crucial role in stabilizing, comfort, and performance of a vehicle. During vehicle braking operation, load transfer happens from rear axle to front axle resulting in shifting of vehicle’s center of gravity towards vehicle front for a momentarily duration, this phenomenon is called diving. This leads to dropping of traction at rear wheel end, resulting in lifting of rear axle with front wheel as pivot causing increase in front to rear weight ratio of vehicle system and moreover, compromising driver safety due to skidding and locking of rear. To minimize this phenomenon’s affect, optimum anti-dive suspension geometry is used to have better rear wheel end traction resulting in improved braking stability. This paper provides methodology for establishing coherence between braking and suspension geometry by providing mathematical model with various suspension geometry and its reaction force on vehicle under braking condition for predicting traction lose at rear wheel end

Patel, Sahil, Pujari, Sachin, Nagrikar, Ravi, Umbare, Deepak

Performance Enhancement of Semi-active Continuous Skyhook Control Using Chaotic Map Particle Swarm Optimization-Based Stability Augmentation System

15-16-01-0002

09/16/2022

Abstract Enhancing the performance of a ride-oriented algorithm to provide ride comfort and vehicle stability throughout different terrains is a challenging task. This article aims to improve the performance of the state-of-the-art continuous skyhook algorithm in coupled motion modes with an optimally tuned stability augmentation system (SAS). The tuning process is carried out using a chaotic map-initialized particle swarm optimization (C-PSO) approach with ride comfort and roll stability as a performance index. A large van model built-in CarSim is co-simulated with a C-PSO algorithm and control system designed in MATLAB. To realize the feasibility and effectiveness of the proposed system, a software-in-loop test is conducted on five complex ride terrains with different dominant vehicle body motion modes. The test results are compared against the passive system, four corner continuous skyhook control, and four corner type-1 fuzzy control. The test results confirm the effectiveness of

Rajasekharan Unnithan, Anand Raj, Subramaniam, Senthilkumar