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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.

Planning for charging in transport missions is vital when commercial long-haul vehicles are to be electrified. In this planning, accurate range prediction is essential so the trucks reach their destinations as planned. The rolling resistance significantly influences truck energy consumption, often considered a simple constant or a function of vehicle speed only. This is, however, a gross simplification, especially as the tire temperature has a significant impact. At 80 km/h, a cold tire can have three times higher rolling resistance than a warm tire. A temperature-dependent rolling resistance model is proposed. The model is based on thermal networks for the temperature at four places around the tire. The model is tuned and validated using rolling resistance, tire shoulder, and tire apex temperature measurements with a truck in a climate wind tunnel with ambient temperatures ranging from -30 to 25 °C at an 80 km/h constant speed.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. Zero Trust (ZT) originated as an Information Technology (IT) principle of “never trust, always verify”; it is the concept that a network must never assume assets can be trusted regardless of their ownership or network location. This research focused on drastically improving security of the cyber-physical vehicle network, with minimal performance impact measured as timing, bandwidth, and processing power. The automotive ZTA was tested using a software-in-the-loop vehicle simulation paired with resource constrained hardware that closely emulated a production vehicle network.

Reconstruction of inline crashes between vehicles with a low closing speed, so-called “low speed” crashes, continues to be a class of vehicle collisions that reconstructionists require specific methods to handle. In general, these collisions tend to be difficult to reconstruct due primarily to the lack of, or limited amount of, physical evidence available after the crash. Traditional reconstruction methods such as impulse-momentum (non-residual damage based) and CRASH3 (residual damage based) both are formulated without considering tire forces of the vehicles. These forces can be important in this class of collisions. Additionally, the CRASH3 method depends on the use of stiffness coefficients for the vehicles obtained from high-speed crash tests. The question of the applicability of these (high-speed) stiffness coefficients to collisions producing significantly less deformation than experimental crashes on which they are generated, raises questions of the applicability.

Truck platooning is an emerging technology that exploits the drag reduction experienced by bluff bodies moving together in close longitudinal proximity. The drag-reduction phenomenon is produced via two mechanisms: wake-effect drag reduction from leading vehicles, whereby a following vehicle operates in a region of lower apparent wind speed, thus reducing its drag; and base-drag reduction from following vehicles, whereby the high-pressure field forward of a closely-following vehicle will increase the base pressure of a leading vehicle, thus reducing its drag. This paper presents a physics-guided empirical model for calculating the drag-reduction benefits from truck platooning. The model provides a general framework from which the drag reduction of any vehicle in a heterogeneous truck platoon can be calculated, based on its isolated-vehicle drag-coefficient performance and limited geometric considerations.

Rapid Urbanisation, in recent times, has created an exponential demand for light commercial vehicles. Electric vehicles are seen as a way to reduce the impact of emissions due to transportation in urban areas. Due to the growth of e-commerce, commercial transportation, and particularly last-mile delivery, is anticipated to increase. In this context, electric light commercial vehicles (eLCVs) have the potential to be a promising solution by tackling the emission impacts, ensuring faster delivery along with ideal running costs and payload capacity. To increase the range of electric vehicles, it has to be designed for lighter weight with optimal performance in order to meet the user requirements. Cargo capacity and payload have to be taken into account while design & validating the vehicle structure under static and dynamic conditions. Simulation driven product development will help the design team to account for the possible design failure cases at system and vehicle level.

Abstract Since the steady-state computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) turbulence models offer low-cost and sensible accuracy, they are frequently utilized for bluff bodies’ external aerodynamics investigations (e.g., upwind, crosswind, and shape optimization). However, no firm certainty is made regarding the best model in terms of accuracy and cost. Based on cost and accuracy aspects, four RANS turbulence models were studied, which are Spalart–Allmaras, realizable k-ε, RNG k-ε, and SST k-ω. Ahmed body with a 25° slant angle benchmark case was introduced for this investigation. Two grids were generated to satisfy the near-wall treatment of each turbulence model. All grid settings were proposed and discussed in detail. Fluid-structure analysis was performed on five different planes.

The Environmental Protection Agency (EPA), in partnership with Research Triangle Institute (RTI International) and Auto Research Center (ARC-Indy), have created digital geometries of commercially available heavy-duty tractor-trailers. The goal of this effort was to improve the agency’s understanding of aerodynamic modeling of modern trucks and to provide opportunities for more consistent engagement on computational fluid dynamics (CFD) analyses. Sleeper and day cab tractors with aerodynamic features and a 53-foot box trailer with aerodynamic technology options were scanned to create high-resolution geometries. The scanning process consisted of a combination of physical scanning with a handheld device, along with digital post-processing. The completed truck geometries are compatible with most commercial CFD software and are publicly available for modeling and analyses.

Brazil is significant grain (soy, corn, beans and rice) producer in the planet and the road transportation is needed even when rail and maritime mode is used. There are opportunities to improve the grain road transportation efficiency. This paper presents one opportunity which is the aerodynamic drag reduction and therefore the fuel and energy consumption reduction on grain road transportation. This paper will discuss some alternatives to reduce aerodynamic drag on such application considering Brazilian market regulation which has a low limit for front axle load (lower than European regulation for instance) and limit the total composition length. As an example of some alternatives to reduce drag there is the frontal area reduction and trailer to cab gap reduction. Some of those alternatives were implemented on a concept truck briefly presented on this paper, which was tested on a real application, this paper will illustrate some of those alternatives implemented.

Volvo Trucks enters electrification's next phase With electric trucks already available, the OEM focuses on refining service and maintenance, expanding EV-certified dealerships and scaling production. Why agriculture will automate before on-highway Danfoss' top autonomy executive says automation will help overcome labor and technological challenges that would otherwise leave billions of dollars' worth of crops rotting in fields. Driver-in-the-loop for off-highway development Industrial and agricultural vehicle engineers can draw many of the same benefits from a driving simulator as passenger-car development teams.

Dry dust testing of vehicles on unpaved dust roads plays a crucial role in the development process of automotive manufacturers. One of the central aspects of the test procedure is ensuring the functionality of locking systems in the case of dust ingress and keeping the dust below a certain concentration level inside the vehicle. Another aspect is the customer comfort because of dust deposited on the surface of the car body. This also poses a safety risk to customers when the dust settles on safety-critical parts such as windshields and obstructs the driver’s view. Dust deposition on sensors is also safety critical and is becoming more important because of the increasing amount of sensors for autonomous driving. Nowadays, dust tests are conducted experimentally at dust proving grounds. To gain early insights and avoid costly physical testing, numerical simulations are considered a promising approach. Simulations of vehicle contamination by dry dust have been studied in the past.

Tire rolling resistance and temperature are the main parameters for the design and driving of the heavy-duty tires due to their effects on fuel economy and safety. In this paper, the influence of many factors on the tire rollingresistance and temperature is studied, including speed, inflation pressure and normal load; the relationship between rolling resistance properties and temperature of heavy tires is studied based on several experiments to explore the physical mechanism and characteristics of tire rolling resistance for heavy-duty vehicles. The effects of the driving time and temperature of the tire on the rolling resistance are performed on tire’s experimental platform, in which the empirical models involved in the driving time and temperature of the tire for the rolling resistance are established using the least square method for fitting the experimental data.

The purpose of this study was to construct driver models using long short-term memory (LSTM) in car-following situations, where other vehicles change lanes and cut in front of the ego vehicle (EGV). The development of autonomous vehicle systems (AVSs) using personalized driver models based on the individual driving characteristics of drivers is expected to reduce their discomfort with vehicle control systems. The driving characteristics of human drivers must be considered in such AVSs. In this study, we experimentally measured data from the EGV and other vehicles using a driving simulator consisting of a six-axis motion device and turntable. The experimental scenario simulated a traffic congestion scenario on a straight section of a highway, where a cut-in vehicle (CIV) changed lanes from an adjacent lane and entered in between the EGV and preceding vehicle (PRV).

Considerable effort is currently being focused on emerging vehicle automation technologies. Engineers are making great strides in improving safety and reliability, but they are also exploring how these new technologies can enhance energy efficiency. This study focuses on the changes in aerodynamic drag associated with coordinated driving scenarios, also known as “platooning.” To draw sound conclusions in simulation or experimental studies where vehicle speed and gaps are controlled and coordinated, it is necessary to have a robust quantitative understanding of the road load changes associated with each vehicle in the platoon. Many variables affect the drag of each vehicle, such as each gap length, vehicle type/size, vehicle order and number of vehicles in the platoon. The effect is generally understood, but there are limited supporting data in the literature from actual test vehicles driving in formation.

Aerodynamic interaction between vehicles on a roadway can modify the fuel use and greenhouse gas emissions of the vehicle relative to their performance under isolated, uniform-wind conditions. A comprehensive wind-tunnel study was undertaken to examine changes to the aerodynamic drag experienced by vehicles in close proximity, in adjacent lanes. Wind-load measurements were conducted for two general configurations: 15%-scale testing with light-duty-vehicle (LDV) models, and 6.7%-scale testing with a heavy-duty vehicle (HDV) model. For the LDV study, a DrivAer model was tested with a proximate AeroSUV model or an Ahmed model at lateral distances representing 75%, 100%, and 125% of a typical highway lane spacing, and for longitudinal distances up to 2 vehicle lengths forward and back. Commensurate measurements were conducted for the AeroSUV model with the proximate DrivAer or Ahmed model.

There have been many studies regarding the stability of vehicles following a sudden air loss event in a tire. Previous works have included literature reviews, full-scale vehicle testing, and computer modeling analyses. Some works have validated physics-based computer vehicle simulation models for passenger vehicles and other works have validated models for heavy commercial vehicles. This work describes a study wherein a validated vehicle dynamics computer model has been applied to extrapolate results to higher event speeds that are consistent with travel speeds on contemporary North American highways. This work applies previously validated vehicle dynamics models to study the stability of a five-axle commercial tractor-semitrailer vehicle following a sudden air loss event for a steer axle tire. Further, the work endeavors to understand the analytical tire model for tires that experience a sudden air loss.

This SAE Standard defines methods and apparatus to evaluate electronic devices for immunity to potential interference from conducted transients along battery feed or switched ignition inputs. Test apparatus specifications outlined in this procedure were developed for components installed in vehicles with 12-V systems (passenger cars and light trucks, 12-V heavy-duty trucks, and vehicles with 24-V systems). Presently, it is not intended for use on other input/output (I/O) lines of the device under test (DUT).

This SAE Standard defines methods and apparatus to evaluate electronic devices for immunity to potential interference from conducted transients along battery feed or switched ignition inputs. Test apparatus specifications outlined in this procedure were developed for components installed in vehicles with 12-V systems (passenger cars and light trucks, 12-V heavy-duty trucks, and vehicles with 24-V systems). Presently, it is not intended for use on other input/output (I/O) lines of the device under test (DUT).

Different tire models are applied in agricultural mobility, but the impacts on the ground are not completely known. Some models of industrial tires, with applications in construction machines, could meet the agricultural demand since there is a shortage offer exclusive models for agriculture. The aim of this research was to analyze in a Fixed Tire Testing Unit (FTTU), under controlled conditions, the performance of two tire types, the first for agricultural construction and the second for industrial construction on two different agricultural soils (two surfaces). The characteristics of the tires evaluated were: 620/75R26 (agricultural tire) and 23.5-25 (industrial tire). The soil used to simulate the agricultural surface were: Red Yellow Latosol and the Distroferric Red Nitosol, chosen because they are representative of agricultural areas in Brazil.