Browse Topic: Road tests
During the pure electric vehicle high speed cruise driving condition, the unsteady air flow in the chassis cavity is susceptible to self-sustaining oscillations phenomenon. And the aerodynamic oscillation excitation could be coupled with the cabin interior acoustic mode through the body pressure relief vent, the low frequency booming noise may occur and seriously reduces the driving comfort. This paper systematically introduces the characteristics identification and the troubleshooting process of the low frequency aerodynamic noise case. Firstly, combined with the characteristics of the subjective jury evaluation and objective measurement, the acoustic wind tunnel test restores the cabin booming phenomenon. The specific test procedure is proposed to separate the noise excitation source. Secondly, according to the road test results, it is inferenced that the formation mechanism of low frequency noise is the self- sustaining oscillation with the underbody shedding vortex feedback
Potential fleet customers had their first hands-on time with “fully production-intent” Bollinger B4 all-electric Class 4 chassis cab trucks during a recent ride-and-drive event. “All of the components, all of the wiring, all of the software and the manner in which the truck is being manufactured is production-intent,” Robert Bollinger, CEO and founder of Bollinger Motors, said in an interview with Truck & Off-Highway Engineering. The Oak Park, Michigan-based electric truck manufacturer chose the Mcity Test Facility, a 32-acre site on the University of Michigan's North Campus in Ann Arbor, for the B4 test drive. Potential customers, Bollinger Motors employees and media attended the event that unfolded in waves over 10 days in September 2023. “Our manufacturing partner, Roush Industries, has produced 20 design-verification B4 vehicles. Five of the vehicles are for marketing purposes and 15 will be used for testing,” Bollinger said, adding that the B4 is slated to enter full production in
One evening earlier this year, I found myself at a convenience-store gas station with eight pumps and one EV fast-charger. I'd been vectored there by the charge provider's phone app. As I exited the freeway, the app indicated the charger was in service and unoccupied. Good news, as the EV that I was test-driving was “running on fumes” - that old-school term for when IC-engine vehicles' fuel tanks are close to dry. “Seek charging immediately,” the vehicle warned! I didn't want to risk trying to make it home, eight miles away
This SAE Standard incorporates driving cycles that produce fuel consumption data relating to Urban, Suburban, and Interstate driving patterns and is intended to be used to determine the relative fuel economy among vehicles and driving patterns under warmed-up conditions on test tracks, suitable roads, or chassis dynamometers.1
The measurement protocol of solid particle number with the lower detection limit (D50) at 10 nm (SPN10) is planned to be implemented in European emission regulations by means of laboratory-grade measurement systems. Furthermore, SPN10 measurement as the real driving emissions (RDE) regulations is under development by defining appropriate technical specifications for the portable emissions measurement system (PEMS). It is under discussion to implement SPN10 limits as one of additional pollutants to the new European emissions regulations, so-called “Euro 7”. As the Consortium for ultra LOw Vehicle Emissions (CLOVE) has proposed, RDE testing by means of PEMS will be the primary means of emissions determination for certification purposes. Measurement equivalency between laboratory-grade emissions measurement systems and PEMS is still important due to the necessity of validation in laboratories before on-road testing by comparing determined emissions by both. The current draft technical
Many chassis and powertrain components in the transportation and automotive industry experience multi-axial cyclic service loading. A thorough load-history leading to durability damage should be considered in the early vehicle production steps. The key feature of rubber fatigue analysis discussed in this study is how to define local critical location strain time history based on nominal and complex load time histories. Material coupon characterization used here is the crack growth approach, based on fracture mechanics parameters. This methodology was utilized and presented for a truck engine mount. Temperature effects are not considered since proving ground (PG) loads are generated under isothermal high temperature and low frequency conditions without high amounts of self-heating. This novel methodology for fatigue life calculation involves finding independent load channels and mapping all load history through converting single or multichannel load-displacement history into stress
In a military off-road vehicle, generally designed to operate in an aggressive operating environment, the typical comfort requirements for trucks and passenger cars are revised for robustness, safety and security. An example is the cabin space optimisation to provide easy access to many types of equipment required on-board. In this field, racks hung to the cabin chassis are generally used to support several electronic systems, like radios. The dynamic loads on a rack can reach high values in the operative conditions of a military vehicle. Rack failures should be prevented for the safety of driver, crew and load and the successful execution of a mission. Therefore, dynamic and durability tests of these components, including the fixtures to the vehicle, are required. The capability to apply in a laboratory a dynamic load equivalent to the one experienced in a real mission opens the possibility to make durability tests in a controlled environment, to repeat them according to a defined
This SAE Recommended Practice provides test performance requirements for air disc brake actuators for service and combination service parking brake actuators with respect to function, durability, and environmental performance when tested according to SAE J2902
In this work, tailpipe carbon monoxide emission from a gasoline powertrain case study vehicle was analyzed for off-cycle (i.e., on road) driving to develop a virtual sensor. The vehicle was equipped with a portable emissions measurement system (PEMS) that measured carbon monoxide concentration and exhaust volumetric flowrate to calculate the mass of carbon monoxide emitted from the tailpipe. The vehicle was also equipped with a tailpipe electrochemical NOx sensor, and a correlation between its linear oxygen signal and the PEMS-measured carbon monoxide concentration was observed. The NOx sensor linear oxygen signal depends on the concentration of several reducing species, and a machine learning model was trained using this data and other features to target the PEMS-measured carbon monoxide mass emission. The model demonstrated a mean absolute percentage error (MAPE) of 19% when using 15 training drive cycles. Finally, a virtual carbon monoxide sensor was developed by removing the
Radar scene emulation helps bridge the gap between simulation and real-world testing of autonomous systems for SAE Level 4 capability. The vision of fully autonomous vehicles (SAE Levels 4 and 5) is fast approaching. Making this vision a reality requires automotive OEMs to move beyond the current levels of vehicle autonomy to deliver on the promise of highly efficient transportation systems, more driver freedom and improved passenger safety. While road testing is a vital part of the development process, the cost, time and challenge of repeatability makes relying on real-world road testing alone unrealistic. Using this approach, it would take hundreds of years for vehicles to be reliable enough to navigate urban and rural roadways safely 100% of the time
Energy flow control and management in a vehicle is an essential aspect of the design process. These solutions are particularly important in the case of vehicles that do not have an external energy source, such as railway vehicles equipped with innovative energy storage technologies. The article presents analyzes of the theoretical energy consumption in a three-car passenger rail vehicle of Polish production, which was equipped with electric energy storage for the purposes of the simulation. An algorithm was developed in the Matlab program for research purposes, which was used to calculate the energy flow in a vehicle traveling along the test route between stations A and B, 73.5 km long, with 18 intermediate stations. During one simulation, the vehicle travels this route back and forth. The article presents the results of six theoretical test runs, which differed in the charging procedure of the vehicle energy storage systems during the travel along the test route. For the test drive
Emissions from motor vehicles are generally recognized to pollute the outside air, with negative effects on human health and the environment. Little is known about the extent to which these pollutants enter the interior of the vehicles through their ventilation systems. The cabin air quality inside vehicles is very lightly regulated around the world, and there is no recognized standard method for measuring pollution ingress. This article tests the effectiveness of a method originally proposed in an SAE paper in 2019 for characterizing the degree of particle ingress. This cabin air quality index is hypothesized to give a repeatable, characteristic value for the vehicle to reduce in-cabin pollutant concentration compared to outside pollutant concentration, which may be suitable for inter-vehicle comparison. To test the method, a series of real-world on-road tests were conducted in Germany with three different types of measurement equipment, two different drivers, and two different routes
The parameter setting has a great influence on the noise reduction performance of the road noise active control (RNC) system. This paper analyzes and optimizes the parameters of the RNC system. Firstly, the model of the RNC system is established based on the FxLMS algorithm. Based on this model, taking the maximum noise reduction as the evaluation index, the sensitivity analysis of convergence coefficient, filter order, and reference signal gain was carried out using the Sobol method with the data measured by a real vehicle on asphalt pavement at 40km/h. The results show that there is no significant interaction between the three parameters. Then, using the idea of orthogonal experiment, the simulation results of the control model are analyzed by taking the maximum noise reduction as the evaluation index. It is found that the convergence coefficient has the greatest effect on the maximum noise reduction, followed by the filter order, and the reference signal gain has the least effect
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