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Heavy Vehicle Event Data Recorders (HVEDRs) have the ability to capture important data surrounding an event such as a crash or near crash. Efforts by many researchers to analyze the capabilities and performance of these complex systems can be problematic, in part, due to the challenges of obtaining a heavy truck, the necessary space to safely test systems, the inherent unpredictability in testing, and the costs associated with this research. In this paper, a method for simulating vehicle speed sensor (VSS) inputs to HVEDRs to trigger events is introduced and validated. Full-scale instrumented testing is conducted to capture raw VSS signals during steady state and braking conditions. The recorded steady state VSS signals are injected into the HVEDR along with synthesized signals to evaluate the response of the HVEDR. Brake testing VSS signals are similarly captured and injected into the HVEDR to trigger an event record.

An experiment is carried out to measure creep groan of a drum brake located in a trailer axle of a truck. The noise nearby the drum brake and accelerations on brake shoes, axle and trailer frame are collected to analyze the occurring conditions and characteristics of the creep groan. A multi-body dynamics model with 1/4 trailer chassis structures is established for analyzing brake component vibrations that generates the creep groan. In the model, the contact force between brake cam and brake shoes, the contact friction characteristics between brake linings and inner circular surface of brake drum, and the properties of chassis structure are included. Dynamic responses of brake shoes, axle and trailer frame during the braking process are estimated using the established model and the responses are compared with the measured results, which validate the model.

To improve the braking energy recovery rate of pure electric garbage removal vehicles and ensure the braking effect of garbage removal vehicles, a strategy using particle swarm algorithm to optimize the regenerative braking fuzzy control of garbage removal vehicles is proposed. A multi-section front and rear wheel braking force distribution curve is designed considering the braking effect and braking energy recovery. A hierarchical regenerative braking fuzzy control strategy is established based on the braking force and braking intensity required by the vehicle. The first layer is based on the braking force required by the vehicle, based on the front and rear axle braking force distribution plan, and uses fuzzy controllers.

The thermal behavior of the electric axle is an essential indicator which requires certain attention during the development process. Due to the complexity of heat generation mechanism and heat transfer boundary conditions, it is difficult to accurately predict the axle’s temperature, especially in real driving conditions. In this paper, a comprehensive 1D model is developed to simulate its heat transfer process effectively and accurately. The heat transfer model is developed based on the thermal network method, and the electric axle is divided into thermal mass according to its heat transfer characteristics. The heat generation model, which accounts for meshing loss, bearing loss, churning loss, and windage loss, exchanges heat flux and oil temperature information with the heat transfer model to take into account the effect of lubricating oil temperature on power loss.

Bicycle computers record and store global position data that can be useful for forensic investigations. The goal of this study was to estimate the absolute error of the latitude and longitude positions recorded by a common bicycle computer over a wide range of riding conditions. We installed three Garmin Edge 530 computers on the handlebars of a bicycle and acquired 9 hours of static data and 96 hours (2214 km) of dynamic data using three different navigation modes (GPS, GPS+GLONASS, and GPS+Galileo satellite systems) and two geographic locations (Vancouver, BC, Canada and Orange County, CA, USA). We used the principle of error propagation to calculate the absolute error of this device from the relative errors between the three pairs of computers. During the static tests, we found 16 m to 108 m of drift during the first 4 min and 1.4 m to 5.0 m of drift during a subsequent 8 min period. During the dynamic tests, we found a 95th percentile absolute error for this device of ±8.04 m.

Creating a 3-dimensional environment using imagery from small unmanned aerial systems (sUAS, or unmanned aerial vehicles -UAVs, or colloquially, drones) has grown in popularity recently in accident reconstruction. In this process, ground control points are placed at an accident scene and an sUAS is flown over an accident site and a series of overlapping, high resolution images are taken of the site. Those images and ground control points are then loaded onto a computer and processed using photogrammetric software to create a 3-dimensional point cloud or mesh of the site, which then can be used as a tool for recreating an accident scene. Many software packages have been created to perform these tasks, and in this paper, the authors examine RealityCapture, a newer photogrammetric software, to evaluate its accuracy for the use in accident reconstruction. It is the authors’ experience that RealityCapture may at times produce point clouds with less noise that other software packages.

Load-carrying transportation has recently increased due to cargo and online home shopping. As a result, there is a growing demand for vehicles that can pass through narrow streets and carry loads for short distances. Electric vehicles are vital in the automotive industry due to their zero emissions and further promotion through new regulations. This study is focused on determining the spring coefficients of helical springs for a micro-truck vehicle, which will be used for cargo transportation and has a leaf spring with a specific spring coefficient on the rear axle and an independent double wishbone suspension system on the front axle. In addition to being vehicles with low weight values, micro-trucks have the axle capacity required for urban transportation due to their low track width and dimensions. Correctly determining the leaf spring is essential as it will directly affect the loads on the suspension system, wheel life, energy consumption, and comfort level.

When a specialty tractor is operated by mounting the front loader or backhoes, the loads are distributed proportionately to the front and rear axles. The maximum load and fatigue life were identified as the main parameters in predicting fatigue failure. This paper mainly focuses on predicting front axle loads and fatigue life in front loader applications. To design a new front axle for the loader application, an existing front axle assembly that was designed for orchard, sprayer, and small farm application is selected for study and to extend it for front loader application with minimal design modifications. The major challenge is to estimate the dynamic loads coming to the front axle due to the front loader application and validate it for a different set of load cases as per the design verification plan. Hence a methodology was framed to estimate the actual loads using MBD, validate with field measurements, and verify the new front axle design using those loads in FEA.

SAE J115 specifies the relevant ISO standards for application to safety labels for use on off-road work machines as defined in SAE J1116.

The cost of fuels used for automobile are rising in India on account of high global crude oil prices. The fuel cost constitutes major portion of total cost of operation for Heavy commercial vehicles. Hence, the trend is to carry the goods transport through higher payload capacity rigid/straight trucks that offer lower transportation cost per unit of goods transported. This is driving the design of multi-axle heavy trucks that have lift axles. In addition, improved network of highways and road infrastructure is leading to increase in average operating speed of heavy commercial vehicles. It has made increased focus on occupant as well as road safety while designing the heavy trucks. Hence, the analysis of lift axle suspension from the point of view of vehicle handling and stability is essential. There are two basic kinds of lift axle designs used in heavy commercial vehicles: self-steered lift axle having single tire on each side and non-steered lift axle with dual tires on each side.

The Heavy Duty live rear axles in commercial vehicle helps to transmit the drive to the rear wheels and also carries vehicle load. The rear axle along with wheel assembly consists of axle casing, differential unit, half shafts, wheel hub, brake drum, brake chamber and wheels. It is one of the major safety critical element in any commercial vehicle. Based on the suspension type, rear axle housing also carries V rod & radius rod mountings & Spring Seat /Wear pad / Rubber Bolster (in case of bogie suspension). This paper abbreviates the contribution of bogie suspension seating configurations & V-rod Forces on life of heavy duty bogie rear axle casing. In-service DRT hot spot observations were reported on heavy duty rear axle on few models with bogie suspension. In order to find the root cause, devising a proper testing and analysis method is of prime importance. An extensive effort was made to device test methodology based on customer application and field visits.

Climate change due to global warming are major concerns. Electric vehicles are one of the promising technologies to curb the climate change by reducing CO2 emissions significantly. Electric vehicle component selection is a complex process, which has to fulfil multiple requirements with trade-off between performance & efficiency, efficiency & cost, performance & NVH, packaging & performance etc. In addition, E-drive selection in passenger & commercial vehicle is different due to application difference. Hence, it is a great challenge to select right E-Drive comprising motor, MCU and overall gear ratio to meet EV program constraints and targets. This study focuses on criterion used for selecting an E-Drive system comprising motor, MCU and overall gear ratio for electric vehicles in commercial and passenger vehicle segments.

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Abstract The drone logistics distribution method, with its small size, quick delivery, and zero-touch, has progressively entered the mainstream of development due to the global epidemic and the rapidly developing global emerging logistics business. In our investigation, a drone and a delivery man worked together to complete the delivery order to a customer’s home as quickly as possible. We realize the combined delivery network between drones and delivery men and focus on the connection and scheduling between drones and delivery men using existing facilities such as ground airports, unmanned stations, delivery men, and drones. Based on the dynamic-vehicle routing problem model, the establishment of a delivery man and drone with a hybrid model, in order to solve the tarmac unmanned aerial vehicle for take-out delivery scheduling difficulties, linking to the delivery man and an adaptive large neighborhood search algorithm solves the model.

This study intends to improve the design of front axles for heavy commercial vehicles, with a major goal of reducing weight while maintaining mechanical strength. The front axle is critical in supporting the weight of the vehicle and facilitating steering while effectively absorbing shocks generated by differences in road surfaces. To achieve these requirements, a front axle beam that minimizes weight, fuel consumption, and stress on the load-carrying member must be designed. In this work, finite element analysis (FEA) techniques are used using CATIA software to assess the structural and mechanical attributes of several front axle designs. The purpose is to pick the best front axle shape depending on specific load situations and driving torque needs. The influence of alternative component shapes on stress and strain distribution is evaluated using surface changes and ANSYS Workbench numerical simulation software.

This document is intended to supplement the SAE J1939 documents by offering the SAE J1939 information in a form that can be sorted and search for easier use.

Abstract Vehicle vibration is the key consideration in the early stage of vehicle development. The most dynamic system in a vehicle is the powertrain system, which is a source of various frequency vibration inputs to the vehicle. Mostly for powertrain mounting system design, only the uncoupled powertrain system is considered. However, in real situations, other subsystems are also attached to the powertrain unit. Thereby, assuming only the powertrain unit ignores the dynamic interactions among the powertrain and other systems. To address this shortcoming, a coupled powertrain and driveline mounting system problem is formulated and examined. This 16 DOF problem is constructed around a case of a front engine-based powertrain unit attached to the driveline system, which as an assembly resting on other systems such as chassis, suspensions, axles, and tires.

This document is intended to supplement the SAE J1939 documents by offering the SAE J1939 information in a form that can be sorted and search for easier use.

This SAE Recommended Practice pertains to blast cleaning and shot peening and provides for standard cast shot and grit size numbers. For shot, this number corresponds with the opening of the nominal test sieve, in ten thousandths of inches1, preceded by an S. For grit, this number corresponds with the sieve designation of the nominal test sieve with the prefix G added. These sieves are in accordance with ASTM E11. The accompanying shot and grit classifications and size designations were formulated by representatives of shot and grit suppliers, equipment manufacturers, and automotive users.

This SAE Recommended Practice is intended for hubs and spoke wheels used on Class 6, 7, and 8 truck/truck-tractor non-powered front axles, powered and non-powered rear axles and trailer axles, for which bearing setting is manually adjusted. Assemblies using spacers to control bearing preload and endplay may differ in geometry and bearing componentry.