Browse Topic: Electric vehicles
SiC-based power devices are favored for high-voltage and high-power applications due to their superior material properties. However, the demand for higher breakdown voltages and improved channel mobility presents significant challenges to the etching process, especially the micro-trenching effect. In this study, etching results from inductively coupled plasma (ICP) have been presents, which focused on using various SF6/O2/Ar gas ratios to eliminate micro-trenching effect. The profile analysis of micro-trench was taken by cross-sectional scanning electron microscopy (SEM). The results demonstrate that micro-trenches primarily originate from the coupling effect between ion multi-reflection from sidewalls and redeposition of etch byproducts. Based on this mechanism, we propose a quasi-Bosch process: a combined polymerization and etching step in oxygen-fluorine-rich plasma deposits polymer on exposed SiC and the mask, while removing it from the structure bottom via ion bombardment to enable etching and passivation; then alternates with a short fluorine-plasma step, which consumes sidewall polymer through ion incidence and prevents SiFxOy charge accumulation, cycle etching gradually deepens the structure without micro-trenches. Different gas ratios and etching time not only change the plasma energy distribution but also affect the temporal synchronization between etching and passivation steps. This approach reduces the special demands on ICP equipment capabilities while achieving superior trench profiles. The optimal etching conditions produced a micro-trench-free SiC structure with a vertical sidewall angle and a surface roughness of less than 1 nm. This methodology and resulting structures significantly advance the manufacturability of high-performance SiC power devices, enabling next-generation applications in electric vehicles and grid infrastructure where device yield and reliability are paramount.
This SAE Surface Vehicle Technical Information Report, SAE J2836/4, establishes diagnostic use cases between plug-in electric vehicles (PEV) and the electric vehicle supply equipment (EVSE). As PEVs are deployed and include both plug-in hybrid electric (PHEV) and battery electric (BEV) vehicle variations, failures of the charging session between the EVSE and PEV may include diagnostics particular to the vehicle variations. This document describes the general information required for diagnostics and SAE J2847/4 will include the detail messages to provide accurate information to the customer and/or service personnel to identify the source of the issue and assist in resolution. Existing vehicle diagnostics can also be added and included during this charging session regarding issues that have occurred or are imminent to the EVSE or PEV, to assist in resolution of these items.
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 electronics is not formally specified in this document. This document will be published as a set of steps. The intent of step 1 was to record as much information on “what we think works” and publish. The intent of step 2 is to provide refinement and missing pieces to step 1, with a an eye to early testing. This version is step 2, with the aim of providing a communication protocol for home chargers.
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.
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 arrangement that significantly reduces the uncertainty of measured noise levels. The proposed setup considers spatial variability without compromising comfort or crash safety requirements. By enhancing the precision of tonal noise quantification, this approach provides noise-vibration-harshness (NVH) engineers with a valuable complement to modern software-based tonal analysis methods. The paper discusses the technical implementation constraints and demonstrates the comparability of the new measurement technique with conventional setups.
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 various defined operating conditions. This test rig has been expanded in two ways within the scope of this work. Firstly, the compressor can be either rigidly attached to a dead mass using a VDA mount or measured while suspended freely. Secondly, a new R744-compatible refrigeration circuit has been added to the test rig, enabling compressors operating with the environmentally friendly refrigerant CO₂, which has so far only been used by a few manufacturers in selected models, to be tested. Measurement results obtained using this test rig provide valuable insight into the vibration behavior and sound spectra of the refrigerant compressor's fluid, structural, and airborne noise when operating at different points.
Tire exterior noise has become increasingly critical in vehicle acoustics due to two key developments: updated pass-by noise regulations, which amplify the relative contribution of tire noise, and the rise of Battery Electric Vehicles (BEVs), which lack traditional powertrain noise. Design trends in BEVs—such as increased vehicle mass from battery packs and the widespread use of large-diameter, wide, low-profile tires—further intensify tire noise due to stiffer constructions and altered contact dynamics. A common method for predicting tire noise is the source-transfer-receiver model, where the tire is represented by a set of monopoles with volume velocity Q derived from near-field measurements. Acoustic propagation is modeled via p/Q transfer functions. Despite its simplifications, this approach is practical for vehicle development, enabling clear separation between source and transfer mechanisms and facilitating targeted noise control strategies. In previous work, we proposed a rigorous framework to optimize both the spatial distribution and strength of the monopole sources. Positions were identified using an L1-norm regularization via the Lasso algorithm, promoting sparsity and physical interpretability. Strengths were estimated using an L2-norm Tikhonov regularization, which stabilizes the solution against measurement noise. While the Tikhonov regularization parameter was previously tuned manually through trial and error, we now enhance predictive accuracy by selecting it via a cross-validation technique, ensuring a more robust and data-driven optimization. Besides this, compared to the previous work the approach here is validated for the prediction of both indoor and outdoor pass-by noise, as well as for multiple tire types providing different noise levels. Results demonstrate the method’s robustness, accuracy, and applicability for acoustic development in modern vehicle platforms.
Vehicle electrification and accelerated development cycles create a need for virtual Noise, Vibration and Harshness (NVH) development tools which are fast, precise and, seamlessly interchangeable between development sites, suppliers and OEMs. Component-based Transfer Path Analysis (C-TPA), standardized in ISO 20270:2019, enables independent component characterization and integration with virtual models to predict sound and vibration in new assemblies, referred to as Virtual Prototype Assemblies (VPA). However, conventional measurements are labor-intensive, typically restricted to a small number of samples, and overlook production variability. This paper introduces a fully automated, ISO 20270-compliant C-TPA system for non-rigid test benches, featuring a pre-instrumented test fixture with multiple vibration shakers and sensors automatically linked to a data acquisition system for immediate processing. Components can be characterized within minutes, with blocked forces directly integrated into a VPA workflow, replacing time-intensive in-vehicle testing with a repeatable, operator-independent bench procedure. A case study on an automotive steering system demonstrates the method’s accuracy, repeatability, and efficiency, along with its ability to predict realistic interior sound pressure levels and capture production variability, enabling robust virtual NVH evaluation early in the development cycle.
Electric vehicle subsystems, including powertrains, electric motors, and gearboxes, pose new challenges in achieving stringent acoustic performance targets for both interior and exterior noise. These challenges are intensified by increasingly demanding customer expectations regarding interior acoustic comfort, which encompasses the reduction of intrusive noise sources and the enhancement of overall sound quality across a broad frequency spectrum. A primary concern associated with electric vehicles subsystems is the generation of high-frequency tonal noise, commonly referred to as whine noise, which can significantly impact acoustic performance and passenger comfort. High-frequency whine noise propagates through multiple transmission paths and can be effectively attenuated at the source through encapsulation strategies, which also contribute to broadband noise reduction across a wide frequency spectrum. To predict the acoustic performance of encapsulation, a coupled simulation approach combining the Boundary Element Method (BEM), the Finite Element Method (FEM) and the Poroelastic Finite Element Method (PEM) has been developed. This methodology has been already presented and validated through experimental measurements, demonstrating its acoustic effectiveness in the encapsulation of a generic electric motor housing. While BEM is well-suited for modeling exterior acoustic propagation, standard implementations encounter limitations at high frequencies due to mesh density requirements and computational cost. This work presents hybrid parallelization strategies that integrate frequency-domain decomposition with multi-threading to accelerate BEM H-matrix computations. Frequency decomposition enables parallel processing by distributing independent frequency tasks across multiple processes, while multi-threading enhances performance for fine-grained operations such as matrix assembly and H-matrix compression within each frequency. The processes and improvements enabled by these strategies are discussed and presented within an adapted high-performance computing (HPC) environment.
The deployment of high-power DC charging infrastructure for electric vehicles introduces new challenges in managing noise, particularly in public environments where acoustic comfort and regulatory compliance are essential. Noise emissions from both charging stations and vehicles during charging are a concern for operators of charging parks regarding customer experience and noise immission regulations. AVL employed a structured three-step approach to develop a non-expert tool for assessing the noise radiation of charging stations and vehicles during the charging phase. In a first step, AVL characterized the noise emissions with sound power measurements. Secondly, the measurement results were transferred to the virtual domain. To achieve this, the vehicles and charging station were characterized in the simulation with multiple monopole sources supported by transfer function measurements. This simulation model was validated against the sound power measurement results. After successful correlation of the simulation model, AVL implemented a user-friendly noise mapping tool for predictive planning of charging parks moving from a 3D FEM simulation approach to a simplified noise radiation model according to ISO 9613. Measurements were conducted on a representative high-power DC charging station and two electric vehicles. The vehicle cooling fan was identified as the dominant noise source on the vehicle side, while internal cooling fans of the charging station were the primary contributors to the noise radiated by the charger. Noise emissions were found to increase with higher charging currents, indicating a strong dependency on thermal load. The project established a reusable workflow for acoustic source identification enabling the creation of a scalable database. The noise mapping tool allows easy prediction of noise radiation from multiple charging stations and vehicles during the planning phase of charging parks and supports the design of countermeasures to meet regulatory requirements.
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 evaluation procedure. It discusses how RCA can be applied to different observed phenomena in EDM NVH behavior and detected deviations between the initial model and the measurements, the main influencing parameters, and the identified improvement potential for simulation models.
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