Browse Topic: Maintenance and Aftermarket

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This study presents a novel approach for predicting fuel consumption in heavy-duty vehicles using a Machine Learning-based model, which is based on feedforward neural network (FFNN). The model is designed to enhance real-time vehicle monitoring, optimize route planning, and reduce both operational costs and environmental impact, making it particularly suitable for fleet management applications. Unlike traditional physics-based approaches, the FFNN relies solely on a refined selection of input variables, including vehicle speed, acceleration, altitude, road slope, ambient temperature, and engine power. Additionally, vehicle mass is estimated using a methodology presented elsewhere and is included as an input for a better generalization of the consumption model. This parameter significantly impacts fuel consumption and is particularly challenging to obtain for heavy-duty vehicles. Engine power is derived from both engine torque and speed (RPM), ensuring a direct relationship with fuel
Vicinanza, MatteoPandolfi, AlfonsoArsie, IvanGiannetti, FlavioPolverino, PierpaoloEsposito, AlfonsoPaolino, AntonioAdinolfi, Ennio AndreaPianese, CesareFrasci, Valentino
Launched in 2022, AeroSolfd, a HORIZON Europe project, aims to advance clean urban mobility by developing affordable and sustainable retrofit solutions for gasoline vehicles. This three-year initiative addresses not only tailpipe emissions but also brake emissions and pollution in semi-enclosed environments. Within AeroSolfd, the Swiss-based VERT association focuses on reducing tailpipe emissions using state-of-the-art Gasoline Particulate Filter (GPF) technology featuring an uncoated ceramic multicell wall-flow filter. VERT, in partnership with HJS, CPK, BFH, developed and tested a GPF-retrofit system at Technology Readiness Level 8 (TRL 8). Results demonstrate over 99% filtration efficiency for particles smaller than 500 nm on standard cycles (WLTC) and real-world driving cycles (RDE). Forty-two gasoline vehicles (GDI and PFI) were retrofitted with the GPF retrofit across Germany, Switzerland, Israel, and Denmark over a 6 to 8-month operational period. No issues were observed with
Rubino, LaurettaMayer, Andreas C.Lutz, Thomas W.Czerwinski, JanLarsen, Lars C.
The transition to decarbonized transportation necessitates significant modifications to internal combustion engines for alternative carbon-neutral fuels, particularly hydrogen. The integration of alternative systems is crucial for improving engine control, facilitating real-time engine health monitoring and facilitate early problem detection. This study investigates the potentialities of an ignition system specifically designed for H2 applications, with the integration of a smart coil diagnostic system with the aim to enhance engine performance and control capabilities. Experiments were conducted on a single-cylinder research engine across varying spark advanced, throttle positions, and engine speeds, comparing the novel ignition system with integrated diagnostics against traditional spark plug. Results demonstrate improvements in combustion stability and control when innovative spark plug was employed. Compared to a conventional spark plug, the Hy2Fire® system consistently delivered
Ricci, FedericoPapi, StefanoAvana, MassimilianoDal Re, MassimoGrimaldi, Carlo
This article details the experimental and testing activities of the EU project AeroSolfd, with a particular focus on the project's efforts to reduce combustion-based nanoparticle emissions in exhaust gases for the European fleet of vehicles by developing a GPF retrofit solution. The technical activities undertaken the process of developing such a retrofit are examined in this article. The findings illustrate the viability of reducing nanoparticle levels in gasoline-powered vehicles with the utilization of appropriate GPFs. For this purpose, in addition to a fleet, four vehicles were examined in great detail and underwent the process of obtaining component approval for the particulate filter. The vehicles were measured in a preliminary state, then following the installation of the GPF, and subsequently after several months of continuous field operation. A total of four vehicles were selected for evaluation as a representative subgroup of a larger test fleet of vehicles in the project
Engelmann, DaniloMayer, AndreasComte, PierreRubino, LaurettaLarsen, Lars
Remote monitoring of commercial vehicles is taking an increasingly central position in automotive companies, driven by the growth of the on-road freight transportation sector. Specifically, telematics devices are increasingly gaining importance in monitoring powertrain operability, performance, reliability, sustainability, and maintainability. These systems enable real-time data collection and analysis, offering valuable support in resolving issues that may occur on the road. Moreover, the fault codes, called Diagnostic Trouble Codes (DTCs), that arise during actual road driving constitute fundamental information when combined with several engine parameters updated every second. This integration provides a more accurate assessment of vehicle conditions, allowing proactive maintenance strategies. The principal goal is to deliver an even faster response for resolving sudden issues, thus minimizing vehicle downtime. High-resolution data transmission and failure event information
D'Agostino, ValerioCardone, MassimoMancaruso, EzioRossetti, SalvatoreMarialto, Renato
Electrification of heavy-duty on-road trucks used for regional freight transportation is a viable option for fleets to reduce operation and maintenance costs and lower their carbon footprint. However, there is considerable uncertainty in projecting their daily range because highly variable payload mass, among other factors, confounds battery state of charge (SOC) prediction algorithms. Previous work by the authors proposed an electric vehicle range prediction model based on two parallel recurrent neural networks (RNNs). The first RNN used mean-variance estimation to output a predicted mean and variance, and the second used bounded interval estimation to provide bounds on the SOC required to complete a trip. The dual RNN approach resulted in estimating the remaining range and error bands of the SOC over the route. The previous work was limited because it did not incorporate driving conditions, like road type and ambient temperature, that affect driver behavior and energy consumption
Jayaprakash, BharatEagon, MatthewNorthrop, William F.
Management of battery systems for electric vehicles has great importance to ensure safe and efficient operation. State-of-Charge and State-of-Health (SoH) are fundamental parameters to be taken under control even though they cannot be directly measured during vehicle operation. Some control approaches have gained increasing interest thanks to advances in sensor availability, edge computing and the development of big data. In particular, SoH estimation through machine learning (ML) and neural networks (NNs) has been thoroughly investigated due to their great flexibility and potential in mapping non-linear relations within data. The numerous studies available in the literature either employ different extracted features from data to train NNs, or directly use measurement signals as input. Additionally, many studies available in the literature are based on a limited number of publicly available datasets, which mainly encompass cylindrical battery cells with small capacity. Starting from
Chianese, GiovanniCapasso, ClementeVeneri, Ottorino
The climate emergency has prompted countries to adopt strategies to limit the rise in global temperatures by promoting low-carbon technologies. In this context, hydrogen (H2) can be considered a viable solution, especially in road and marine transportation, where Compression Ignition (CI) internal combustion engines (ICEs) are widely used. Despite its potential to significantly reduce pollutant emissions compared to fossil fuels, hydrogen presents a major challenge for CI engines due to its high autoignition temperature (greater than diesel). To overcome this problem, a novel methodology is proposed to evaluate the feasibility of hydrogen retrofitting. Each engine operating point is simulated as an ideal zero-dimensional (0D) reactor into which a diesel-hydrogen-air mixture is introduced. A fully detailed kinetic mechanism is used to simulate the complex chemical interactions between the two fuels, as well as its significant effect on engine behaviour, obtaining accurate predictions of
Episcopo, DomenicoRossetti, SalvatoreMancaruso, EzioSaponaro, GianmarcoCamporeale, SergioLaera, Davide
For years researchers at the Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) have been developing tools to accelerate the materials discovery and development of new energy storage technologies, including those that can predict the performance of the batteries systems for long-term grid services.
Medical tubing is an essential component of countless healthcare applications, from intravenous (IV) and oxygen lines to catheters and diagnostic equipment. These tubes, often made of clear flexible polymers, must be produced to exacting standards: free of contaminants, strong under pressure, and biocompatible. However, the joining process to connect these tubes can introduce significant manufacturing challenges.
MIT researchers have used 3D printing to produce self-heating microfluidic devices, demonstrating a technique which could someday be used to rapidly create cheap, yet accurate, tools to detect a host of diseases.
This article presents a path planning and control method for a cost-effective autonomous sweeping vehicle operating in enclosed campus. First, to address the challenges from perception, an effective obstacle filtering algorithm is proposed, considering the elimination of false detection and correction of object position. Based on it, the adaptive sampling–based path planner and pure pursuit controller are developed. Not only an adaptive cost-weighting mechanism is introduced by TOPSIS algorithm to determine the desired trajectory as a multi-objective optimization problem, but also the adaptive preview distance is designed according to the trajectory curvature and vehicle state. The real-vehicle tests are implemented in typical scenario. The results show that the 87.8% effective edge-following rate is achieved in curved paths, and 22.93% cleaning coverage is improved for cleaning coverage. Therefore, the proposed method is effective and reliable for cost-effective autonomous sweeping
Lei, WuKunYang, BoPei, XiaofeiZhang, YangZhou, HongLong
Solar panels are composed of dozens of solar cells, which are usually made of silicon. While silicon is the standard, producing and processing it is energy-intensive, making it costly to build new solar panel manufacturing facilities. Most of the world’s solar cells are made in China, which has an abundance of silicon. To increase solar cell production in the U.S., a new, easily produced domestic material is needed. “We’re developing technologies that we can easily produce without spending a ton of money on expensive equipment,” said Juan-Pablo Correa-Baena, an Associate Professor in the School of Materials Science and Engineering.
Warehouse logistics increasingly rely on automation in the form of autonomous mobile robots (AMRs), scanners, complex conveyors, and fleet management systems for seamless operation, but it’s the ubiquitous, century-old pallet that remains the critical support system. Make no mistake, if even one of those thousands of pallets is defective, it can create havoc in the warehouse.
Technological solutions to monitor and manage fleets are important to increase efficiency and reduce cargo transport costs. This work presents a SaaS (Software as a Service) platform for fleet management, aimed at optimizing operational efficiency and improving vehicle safety. It distinguishes itself as an innovative solution by integrating various functionalities related to cargo transport into a unified environment. The platform allows for route tracking, with different alert notifications generated from sensors, virtual geographic fences, driver identification, and smart cameras. Tire management is another critical aspect that encompasses the unique identification of each tire and its association with vehicles, along with monitoring data such as mileage, speed, temperature, pressure, tread wear, retreading, and performance based on distance traveled. Alerts for tire rotation, tread depth measurements, and excessive tread wear enhance performance management, while key performance
Fonseca, Murilo L.Mochiutti, EricRosa, Rodrigo K.Benczik, Paulo H.Gonçalves, Vitor M.Zanolli, Willians S.
This document describes: a The preparatory steps to test experimental Type I fluids according to AMS1424; b The recommendations for the preparation of samples for endurance time testing according to ARP5945; c A short description of the recommended field spray test; d The protocol to demonstrate that Type I fluid can be used with the Type I holdover time guidelines published by the FAA and Transport Canada, including endurance time data obtained from ARP5945; e The protocol for inclusion of Type I fluids on the FAA and Transport Canada lists of fluids; f The protocol for updating the FAA and Transport Canada lists of fluids; g The role of the SAE G-12 Aircraft Deicing Fluids Committee; h The role of the SAE G-12 Holdover Time Committee; and i The process for the publication of Type I holdover time guidelines. This document does not describe laboratory-testing procedures. This document does not include the qualification requirements for AMS1428 Type II, III, and IV fluids (these are
G-12HOT Holdover Time Committee
This document describes: a The preparatory steps to test experimental Type II, III, and IV fluids according to AMS1428 b The recommendations for the preparation of samples for endurance time testing according to ARP5485 c A short description of wind tunnel testing d A short description of the recommended field spray test e The protocol to generate draft holdover time guidelines from endurance time data obtained from ARP5485 f The protocol for inclusion of Type II, III, and IV fluids on the FAA and Transport Canada lists of fluids and the protocol for updating the lists of fluids g The role of the SAE G-12 Aircraft Deicing Fluids Committee h The role of the SAE G-12 Holdover Time Committee i The process for the publication of Type II, III, and IV holdover time guidelines This document does not describe laboratory testing procedures. This document does not include the qualification requirements for AMS1424 Type I fluids (these are provided in ARP6207).
G-12HOT Holdover Time Committee
This document establishes general design criteria, tolerances, and limits of application for tooling, fixtures, and accessories for mounting and driving gas turbine engine rotors on horizontal and vertical balancing machines.
EG-1A Balancing Committee
Vehicles are evolving into Software-Defined Vehicles. The increasing use of automotive High Performance Computers (HPCs) provides more computing power and storage resources in vehicles. This opens possibilities to use more in-vehicle software. However, it also leads to challenges for vehicle diagnostics. Today's diagnostic approaches, based on Diagnostic Trouble Codes (DTCs), are not suitable for software on HPCs. For example, this software is highly variable and updated over time, so predefined DTCs are not dynamic enough. This introduces a degree of ambiguity into the diagnostic processes. Additional diagnostic data are required. In the Cloud, observability approaches are becoming widely used for software. Observability involves examining the availability and performance of an entire software system. To detect failures early, observability data, such as logs, metrics, and traces, are used. This is of interest for vehicle diagnostics as new diagnostic approaches are needed to
Bickelhaupt, SandraHahn, MichaelWeyrich, MichaelMorozov, Andrey
Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of drive system properties. Estimating these properties in the early stages of development is challenging due to the depth of modelling required. In addition, defined requirements play a critical role in drive system sizing. This paper presents a tool chain for the synthesis of new electrified drive concepts, with emphasis on requirements definition and modelling. The requirements definition method combines market analysis with a generalized calculation and estimation approach, providing a novel perspective. In addition, we introduce mass and cost modelling capabilities integrated into the tool chain. The mass model achieves high accuracy, with deviations of only 1.6 % at the vehicle level and 6.1 % at the component level. Finally, the paper examines the mass and cost
Sturm, AxelHenze, Roman
A paper-based diagnostic device can detect COVID-19 and other infectious diseases in under 10 minutes, without the need for sophisticated lab equipment or trained personnel.
A research team has developed DeepNeo, an AI-powered algorithm that automates the process of analyzing coronary stents after implantation. The tool matches medical expert accuracy while significantly reducing assessment time. With strong validation in both human and animal models, Deep-Neo has the potential to standardize monitoring after stent implantation and thus improve cardiovascular treatment outcomes.
Chronic stress can lead to increased blood pressure and cardiovascular disease, decreased immune function, depression, and anxiety. Unfortunately, the tools we use to monitor stress are often imprecise or expensive, relying on self-reporting questionnaires and psychiatric evaluations.
This SAE Standard covers complete general and dimensional specifications for refrigeration tube fittings of the flare type specified in Figures 1 to 42 and Tables 1 to 15. These fittings are intended for general use with flared annealed copper tubing in refrigeration applications. Dimensions of single and double 45 degree flares on tubing to be used in conjunction with these fittings are given in Figure 2 and Table 1 of SAE J533. The following general specifications supplement the dimensional data contained in Tables 1 to 15 with respect to all unspecified details.
Air Brake Tubing and Tube Ftg Committee
The AMS1428 specification defines the technical requirements for Type II, III, and IV aircraft deicing/anti-icing fluids. These non-Newtonian thickened fluids are formulated to effectively remove frost, ice, and snow from aircraft surfaces while offering protection times longer than Type I fluids against refreezing or frozen contamination. The document outlines key performance criteria, such as freezing point, aerodynamic acceptance, and anti-icing performance, alongside environmental properties like biodegradability, aquatic toxicity, biochemical oxygen demand (BOD), and chemical oxygen demand (COD). Operational considerations, including storage stability, materials compatibility, exposure to dry air, dry-out exposure to cold dry air, successive dry-out and rehydration, and physical properties like pH, refraction, and rheological properties (viscosity) are also specified. Additionally, the specification details the required testing methods to evaluate these properties and sets forth
G-12ADF Aircraft Deicing Fluids
The escalating complexity at intersections challenges the safety of the interaction between vehicles and pedestrians, especially for those with mobility impairments. Traditional traffic control systems detect pedestrians through costly technologies such as LiDAR and radar, limiting their adoption due to high costs and static programming. Therefore, the article proposes a customized signalized intersection control (CSIC) algorithm for pedestrian safety enhancement. This algorithm integrates advanced computer vision (CV) algorithms to detect, track, and predict pedestrian movements in real time, enhancing safety at a signalized intersection while remaining economically viable and easily integrated into existing infrastructure. Implemented at a key intersection in Bellevue, the CSIC system achieves a 100% pedestrian passing rate while simultaneously minimizing the average remaining walk time after crossings. The algorithm used in this study demonstrates the potential of combining CV with
Xia, RongjingFang, HongchaoZhang, Chenyang
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