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This SAE Information Report SAE J2836/6 establishes use cases for communication between plug-in electric vehicles and the EVSE for wireless energy transfer as specified in SAE J2954. It addresses the requirements for communications between the on-board charging system and the wireless EV supply equipment (WEVSE) in support of detection of the WEVSE, the charging process, and monitoring of the charging process. Since the communication to the charging infrastructure and the power grid for smart charging will also be communicated by the WEVSE to the EV over the wireless interface, these requirements are also covered. However, the processes and procedures are expected to be identical to those specified for V2G communications specified in SAE J2836/1. Where relevant, the specification notes interactions that may be required between the vehicle and vehicle operator, but does not formally specify them. Similarly, communications between the on-board charging sub-system and the on-board vehicle
Hybrid - EV Committee
This specification covers a blend of chromium carbide and a nickel-chromium alloy in the form of powder.
AMS F Corrosion and Heat Resistant Alloys Committee
This specification covers a corrosion-resistant steel in the form of bars, wire, forgings, and forging stock.
AMS F Corrosion and Heat Resistant Alloys Committee
This document provides recommendations involving BEV battery data retention and battery design that enhance the potential for BEV battery reuse and serviceability and that can improve recyclability. These recommendations have been developed by a group of professionals skilled in the secondary-use of batteries and in the research, development, and manufacture of BEV batteries and battery systems.
Secondary Battery Use Committee
This study focuses on a hydrogen ejector for a proton exchange membrane fuel cell (PEMFC) with a maximum power of 150 kW. Experimental tests were conducted to obtain the operating parameters of the stack under 100 kW and 150 kW conditions, which were used as simulation boundary conditions. A three-dimensional numerical model of the ejector was established and validated. Based on this model, the effects of key structural parameters—including nozzle throat radius (Rnt), nozzle position (NXP), mixing chamber radius (Rm), diffuser outlet radius (Rde), secondary flow inlet radius (Rs), suction chamber radius (Rf), and constant-pressure mixing chamber length (Lpm)—on ejector performance were systematically analyzed. The results indicate that Rnt and Rf are negatively correlated with ejector performance, while Rs and Lpm are positively correlated. In contrast, NXP, Rm, and Rde exhibit an optimal range, leading to a single-peak characteristic in ejector performance. This research provides a
Liu, GuoqingTai, ShupengXi, FuqiangLi, ZongjiJi, ShaoboWang, XiuyuWei, Hui
Stochastic preignition (SPI) or low-speed preignition (LSPI) is an abnormal combustion phenomenon observed in downsized turbocharged direct-injection spark-ignition engines at highly boosted conditions. SPI results from the ignition of the air-fuel mixture from a fuel or oil droplet or a detached deposit before the spark discharge, and its occurrence can lead to extremely high peak pressures and severe knock, which can cause physical damage to the engine. This phenomenon limits the downsizing and boosting potential of direct-injection spark-ignition engines, thereby constraining the efficiency benefits that can be achieved. The propensity for SPI to occur is impacted by engine operating conditions as well as the properties of the fuel, fuel additives, lubricant, and lubricant additives. To mitigate its occurrence, it is important to understand the factors that impact the frequency of SPI events. As this abnormal combustion phenomenon is relatively recent, there was a lack of a standard
Gopujkar, SiddharthDavis, RichardWorm, JeremyTuma, NicShukla, PrajwalReilly, VeronicaChapman, ElanaCiaravino, JosephSeyfried, Philipp
This part of SAE J514 covers general and dimensional specifications for 37 degree flared tube fittings. Also included are 37 degree flared fittings with NPTF pipe threads in Appendix B. These fittings are intended for general application in hydraulic systems on industrial equipment and commercial products. These fittings are capable of providing leak-proof, full flow connections in hydraulic systems operating at working pressures as specified in Table 6. Since many factors influence the pressure at which a hydraulic system will or will not perform satisfactorily, the values shown in Table 6 should not be construed as a guaranteed minimum. For any application, it is recommended that sufficient testing be conducted and reviewed by both the user and fitting manufacturer to assure that performance levels will be safe and satisfactory.
Hydraulic Tube Fittings Committee
This Information Report relates to a special class of automotive adaptive equipment which consists of modifications to the power brake booster systems provided as original equipment of motor vehicles. These modifications are generically called "Reduced Effort Power Brakes" (REPB) The purpose of the modification is to lower the amount of driver effort required to apply the brakes. Retention of reliability, ease of use and maintainability for disabled drivers, passengers, and the general public is of primary concern. Reduced Effort Power Brake modifications should be qualified by the tests referenced in the Recommended Test Procedure. The tests set forth in that procedure should be applied, and failure of a Reduced Effort Power Brake modification to meet those tests should disqualify the modification from the claim of meeting the specifications of this Information Report. Because this is an Information Report, the numerical values for performance measurements presented in this report and
Adaptive Devices Standards Committee
This SAE Recommended Practice is intended to provide basic information on properties and characteristics of high-strength carbon and alloy steels which have been subjected to special die drawing. This includes both cold drawing with heavier-than-normal drafts and die drawing at elevated temperatures.
Metals Technical Committee
When developing a vehicle, the overall body stiffness is an important parameter to be estimated for several automotive attributes. As a complement to the traditional experimental and computational static torsional stiffness assessment, an improved method has been developed to evaluate the body stiffness when driving the vehicle on a test track. This method, valid for both test and simulation, is called Opening Distortion Fingerprint (ODF) and uses the so-called Multi Stethoscope (MSS) to measure the dynamic distortion in each body closure opening and cross section. For evaluating the distortion, from both test and Multi Body Dynamics (MBD) simulation data, the Evaluation-line (E-line) method is used. The E-line method is a linear approach. Consequently, it is only valid in the absence of large rigid body rotations of the vehicle body. Therefore, to assess the validity of the ODF method, it is crucial to identify the frequency at which the distortion results become invalid due to rigid
Olger, EmmaLindkvist, LisaPiiroinen, PetriKarypidis, JohnPena, MiltonBäcklund, JesperAppelgren, PeterMarberg, HenrikUgale, PravinWeber, Jens
This study investigates the NVH characteristics of the spline coupling that connects the motor and reducer shafts in an electric drive unit, using flexible multibody dynamics simulations. Focusing on the source stage of the NVH analysis process, the excitation force magnitude and spline trajectory are examined under various spline design conditions. The study compares spline fit types (side fit vs. major fit), clearance vs. interference conditions, and variations in tooth number and module size. This study analyzes the overall behavior of spline excitation forces under various design conditions, complementing prior research focused mainly on specific causes or manufacturing improvements. Side fit splines exhibit lower first-order excitation forces compared to major fit splines, but significantly higher excitation forces at higher orders. This leads to increased spline trajectory amplitude and amplified whirling of the input shaft. Since the input gear is directly coupled to the input
Kim, Dong-JunHwang, Seung GyuKim, DongheeKim, Seon HyeongLee, SangHanGrant, GeorgeHalse, Christopher
Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current
Girstmair, Josef
The rapid electrification of the automotive industry introduces new challenges in noise, vibration, and harshness (NVH). In particular, in a virtual prototyping phase of the e-vehicles development, the rubber mounts are often one of the key elements to be considered when analysing the structure borne noise contributions. Having an accurate experimental characterization of the mount dynamic stiffness curves is therefore very relevant. However, conventional mount characterization methods are often pushed to their limits, partly due to the use of stiffer bushings, and partly because the frequency range of interest is extended toward higher frequencies. When using inverse substructuring, the dynamic stiffness curves can be obtained from frequency response function measurements. The required test setup consists of excitations and responses, located on each side of the mount via dedicated fixtures. The measured frequency response functions are reduced into 6 degrees of freedom representation
Bianciardi, FabioForrier, BartMinervini, DomenicoBarbieri, MarcoJanssens, Karl
Realistic seat vibration reproduction is essential for delivering authentic haptic cues and enhancing driver immersion in driving simulators. Unlike direct playback of road recordings, simulator applications require vibration synthesis that responds interactively to driver inputs and vehicle dynamics. Reproducing these vibrations at the seat is often complicated by actuator bandwidth limitations and the dynamic behaviour of the seat structure itself, which can alter the intended target response. This work presents vibration synthesis and seat dynamics compensation strategies implemented on a single-axis seat vibration reproduction system equipped with a vertical actuator. Frequency Response Functions (FRFs) were measured to characterise the system dynamics under single-axis excitation. Run-up and coast-down tests were conducted on the seat and compared to target responses measured on an actual vehicle under operational conditions. Several seat dynamics compensation strategies were
Muthu Chaiphas, Joshua DanielCuenca, JacquesBianciardi, FabioColangeli, ClaudioDeckers, ElkeDenayer, HervéJanssens, Karl
The effect of backing polyurethane (PU) foam material properties on the insertion loss of acoustic insulation pads was investigated. First, the material properties affecting the resonant frequency, which mainly determines the insertion loss, were theoretically identified, and practical methods for calculating both the resonant frequency and the insertion loss of the insulation pad were developed. These methods were then applied to evaluate how changes in material properties influence the resonant frequency and insertion loss of the insulation pad. It was found that Young’s modulus, Poisson’s ratio, and thermal characteristic length are the primary material properties that affect these outcomes. The optimal levels of these properties, which are beneficial for interior noise reduction, are derived and presented in this study.
Chae, Ki-SangLee, MoonseokKim, Hyunwoo
The virtual development of Electric Drive Modules (EDMs) for Battery Electric Vehicles (BEVs) requires proven and predictive methodologies. One part of the development investigates the vibro-acoustic assessment for the low- and high-frequency ranges within the targeted operating range. The efficient use of such a methodology requires an understanding of the accuracy and validity of the achievable results, as well as the derivation of suitable improvement measures for goals that have not been achieved. The use of reference data from experimental investigations and a detailed root cause analysis (RCA), to directly link a specific response and behavior to the excitations, modal content, and transfer functions, is an essential and non-trivial part of the methodology development. This paper describes the development of such a methodology using the example of a new EDM virtual model for Noise, Vibration and Harshness (NVH) analysis, including the simulation approach, validation, and
Klarin, BorislavPevec, DenisResch, ThomasEsposito, SaraD'Alessandro, VincenzoSpanu, Giorgio
This work presents a modular engineering methodology (DiPhyBa - Digital Physical Balance) for the virtual validation of Noise, Vibration, and Harshness (NVH) performance in automotive development. The approach addresses the inefficiency of repeated physical testing across vehicle variants by introducing a structured two-phase process—Launcher and Reskin—centered on quantitative performance indicators with formal acceptance thresholds. In the Launcher phase, a digital replica of the base vehicle is built and iteratively correlated with physical test data. Validation is governed by objective indicators of confidence, conformity, and correlation, each evaluated against predefined thresholds. Once validated, the model becomes a certified reference, enabling its reuse across derivative configurations in the Reskin phase. Physical testing is only required if indicators fall below threshold, with a final gate test on pre-series vehicles ensuring industrial robustness. DiPhyBa formalizes the
Celiberti, LuciaCamia, Andrea
Because of automotive electrification, fan system noises previously hidden by the internal combustion engine could become key contributors to the overall noise behavior. Metrics like overall sound pressure level or Loudness are first order metrics enabling noise ranking. Yet, second order factors, that are relevant to assess annoyance, are not correctly described using a single criterion. This paper studies the applicability of various psychoacoustic annoyance models in an attempt to address the subjective perception of sound quality. Based on pairwise comparisons through a jury test with a set of 8 noises at similar overall levels, the combined impact of several psychoacoustics metrics was previously determined. This computation includes a signal modulation metric, a frequency content balance and a tonal criterion. To complete this approach, the correlation for fan system noise annoyance ranking based on this jury test is compared with several psychoacoustic annoyance criteria. These
Scouarnec, DenisBennouna, Saad
The increasing electrification of vehicles means that heating, ventilation and air conditioning systems have a broader range of tasks and a different priority assessment. In electric cars, air conditioning systems are not only responsible for cooling the passenger compartment, but also for controlling the battery temperature, particularly during rapid charging, which represents a high-load operating point. Furthermore, achieving high thermodynamic efficiency is desirable, as this directly impacts the range of electric cars. The elimination of the combustion engine as a major source of noise prioritizes the noise, vibration and harshness behavior of the refrigerant compressor for product selection. To investigate the vibration and acoustic behavior, as well as the fluid dynamic forces resulting from the cyclic compression principle of an electric refrigerant compressor, a test rig was developed that allows compressors to be operated and measured in isolation in an anechoic chamber under
Beer, GabrielSaur, LukasSchwarz, ManuelZemsch, StefanBecker, Stefan
Achieving best-in-class Noise, Vibration, and Harshness (NVH) in electric powertrains demands a paradigm shift in development methodology. This paper presents a practice-oriented overview of simulation methods in NVH development methodology for electric drive units. This includes target cascading and multi-objective optimisation, and by attacking NVH at the source using KPIs early in the design cycle, significant reductions in development time and reliance on traditional testbed loops are realised. Machine learning (Neural Network) algorithms are utilized to find the best-in-class design, using multi-objective optimisation as well as refining simulation accuracy by adding tolerance effects while target cascading ensures alignment of system-level performance objectives down to subsystem contributions. Combined, these strategies enable rapid and robust NVH optimisation, using simulation for next-generation electric powertrain development. Several applications and real-life examples
Mehrgou, MehdiGarcia de Madinabeitia, InigoGraf, BernhardGojo, Josef
The simulation of structure-borne energy flow within a full vehicle trimmed body at mid and high frequencies has always been a challenge due to the large computational cost associated with standard deterministic simulations. This is a particularly pressing problem given that the electrification of the vehicles is extending the presence of structure-borne sources to higher frequencies. While the improvement of computational hardware has allowed OEMs to shift the limit of standard Finite Element (FE) approaches to higher frequencies, no methods have been proposed in the literature that tackle the full frequency range for industrial-sized problems. In this paper, a simulation methodology that uses wave-based processing of the original low-frequency finite element input deck to compute the coupling loss factors is proposed to model structure-borne noise in complex systems at mid and high frequencies. The methodology is validated against numerical and experimental data.
Errico, FabrizioLegault, JulienMordillat, PhilippeZerrad, Mehdi
In vehicles with electrified powertrains, high-frequency tonal noise components have become increasingly prominent and can be perceived as particularly annoying by the driver. While recent advancements in international standardization — such as ECMA-74 [1] and ECMA-418 [2] — have led to powerful new algorithms for tonal noise visualization and analysis, including Tonality-Heatmaps, the measurement side still lacks sensor setups that adequately reflect the spatial sensitivity of noise, especially for tonal components. This challenge is amplified in enclosed vehicle cabins, where room modes create local minima and maxima that become increasingly dense at higher frequencies. As a result, even small head movements can lead to noticeable differences in perceived tonal noise. Current measurement approaches do not sufficiently account for this spatial variability. This contribution addresses the absence of tailored solutions for the driver’s position by introducing an improved microphone
Schecker, DanielRittenschober, Thomas
In this study, we propose a methodology for predicting the acoustic modes and natural frequencies of a sedan using artificial intelligence and demonstrate the feasibility of controlling its acoustic characteristics by modifying the hole distribution of the package tray. In typical sedan structures, the cabin cavity and trunk cavity are acoustically coupled through holes in the package tray. The distribution of these holes significantly affects the natural acoustic modes and frequencies of the vehicle. However, once the exterior shape of the vehicle is finalized during the design stage, options for structural modifications to mitigate noise issues caused by these modes become extremely limited. To address this challenge efficiently, we develop a deep learning-based neural network model trained on data derived from a simplified acoustic analysis model of a sedan that includes a package tray. Finite element analysis is performed to generate acoustic modes and natural frequencies, which
Lee, Jin WooCho, JaehoNam, YounsicHan, Yongha