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On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

Design for Manufacturing and Assembly (DFM+A), pioneered by Boothroyd and Dewhurst, has been used by many companies around the world to develop creative product designs that use optimal manufacturing and assembly processes. Correctly applied, DFM+A analysis leads to significant reductions in production cost, without compromising product time-to-market goals, functionality, quality, serviceability, or other attributes. In this two-day course, you will not only learn the Boothroyd Dewhurst Method, you will actually apply it to your own product design!

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Now Available from SAE International, SAE OnQue is a revolutionary digital standards solution that optimizes the way automotive and aerospace engineers access standards.

From SAE International, SAE MobilityRxiv is a free online preprint server and sharing service for English-language preprints in the mobility/transportation field

SAE J3078 provides test methods and criteria for the evaluation of the operator enclosure environment in earth-moving machinery as defined in ISO 6165. SAE J3078/1 gives the terms and definitions which are used in other parts of SAE J3078. It is applicable to Off-Road Self-Propelled Work Machines as defined in SAE J1116 and tractors and machinery for agriculture and forestry as defined in ANSI/ASAE S390.

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.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core.

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.

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.

Wrap around distance (WAD) is an important index to evaluate the contact position between pedestrian head and vehicle, and is also one of the key parameters of pedestrian accident reconstruction. The purpose of this paper is to explore whether the pedestrian headform testcan reflect the distribution of head injury in the real world. Firstly, in order to study the distribution of pedestrian head WAD in road accidents in China, a head WAD prediction model was established using logistic regression based on pedestrian height and vehicle collision speed. Secondly, in order to study the distribution of the risk of severe head injuries among pedestrians in accidents, the frequency of pedestrian head impact and the proportion of pedestrian head injury were counted respectively for sedans and SUVs. Subsequently, a risk curve for severe head injuries was constructed based on the head impact frequency and the proportion of severe injuries, utilizing a method that incorporates joint probability.

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.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

Compared to passenger cars, commercial vehicles have relatively high fuel and energy consumption, relatively high average annual driving mileage, and a wide range of use. Therefore, energy-saving management of commercial vehicles is crucial. For multi-axle distributed pure electric drive commercial vehicles, a dynamic allocation control strategy for driving torque based on energy consumption optimization is proposed. First, the basic idea of the driving torque distribution control strategy was analyzed and a relevant mathematical model was established. Then, the offline optimization of the distribution coefficients of the driving torque for each axle was carried out through a genetic algorithm, and the entire vehicle driving force distribution strategy using the distribution coefficients as an online lookup table was determined.

Abstract The two-branch exhaust of an asymmetric twin-scroll turbocharged engine are asymmetrically and periodically complicated, which has great impact on turbine matching. In this article, a matching effect of turbine speed parameter on asymmetric twin-scroll turbines based on the exhaust pulse energy weight distribution of a heavy-duty diesel engine was introduced. First, it was built as an asymmetric twin-scroll turbine matching based on exhaust pulse energy distribution. Then, by comparing the average matching point and energy matching points on the corresponding turbine performance map, it is revealed that the turbine speed parameter of energy matching points was a significant deviation from the turbine speed parameter under peak efficiency, which leads to the actual turbine operating efficiency lower than the optimal state.

Abstract The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

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