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Given the fast changing market demands, the growing complexity of features, the shorter time to market, and the design/development constraints, the need for efficient and effective verification and validation methods are becoming critical for vehicle manufacturers and suppliers. One such example is fault-tree analysis. While fault-tree analysis is an important hazard analysis/verification activity, the current process of translating design details (e.g., system level and software level) is manual. Current experience indicates that fault tree analysis involves both creative deductive thinking and more mechanical steps, which typically involve instantiating gates and events in fault trees following fixed patterns. Specifically for software fault tree analysis, a number of the development steps typically involve instantiating fixed patterns of gates and events based upon the structure of the code. In this work, we investigate a methodology to translate software programs to fault trees.

As an annual subscription, the Wiley Cyber Security Collection Add-On is available for purchase along with one or both of the following: Wiley Aerospace Collection Wiley Automotive Collection The titles from the Wiley Cyber Security Collection are included in the SAE MOBILUS® eBook Package. Titles: Network Forensics Penetration Testing Essentials Security in Fixed and Wireless Networks, 2nd Edition The Network Security Test Lab: A Step-by-Step Guide Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis Applied Cryptography: Protocols, Algorithms and Source Code in C, 20th Anniversary Edition Computer Security Handbook, Set, 6th Edition Threat Modeling: Designing for Security Other available Wiley collections: Wiley SAE MOBILUS eBook Package Wiley Aerospace Collection Wiley Automotive Collection Wiley Computer Systems Collection Add-On (purchasable with the Wiley Aerospace Collection and/or the Wiley Automotive Collection)

This technical paper collection discusses the modeling, analysis, and validation of commercial vehicle chassis, suspension, and tire modeling and simulation. Topics include commercial vehicle dynamics; chassis control devices such as ABS, traction control, yaw/roll stability control, and their interaction with suspension controls; modeling and simulation of ride comfort, as well as passive and active suspension control methodologies. Authors are encouraged to discuss the validation of their modeling and simulation.

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract This study proposes a method for the rapid detection and location of cavity defects in ballastless track structures of high-speed railways in service. First, the propagation law of air-coupled ultrasonic Lamb waves in the ballastless track structure is studied. Theoretical calculation results show that the ultrasonic Lamb wave group velocity of the A2 mode in the track plate is 4000 m/s. Then, the excitation and reception methods of the air-coupled ultrasound are studied. Theoretical and experimental results show that the A2 mode Lamb wave can be generated by the 3.8° oblique incidence of the ballastless track structure. Finally, an experimental system for air-coupled ultrasonic testing is constructed. A pair of air-coupled ultrasonic probes is used to provide excitation and reception Lamb wave signals at an inclined angle of 3.8°, 20 mm away from the surface of the track plate, and 40 mm/step along the scanning direction.

This document will provide recommendations to vehicle manufacturers and component suppliers in securing the SAE J1939-13 connector interface from the cybersecurity risks posed by the existence of this connector.

The objective of the project was to conduct controlled test-track studies of solutions for achieving higher fuel efficiency and lower greenhouse gas emissions in the trucking industry. Using vehicles from five Canadian fleets, technologies from 12 suppliers were chosen for testing, including aerodynamic devices and low rolling resistance tires. The participating fleets also decided to conduct tests for evaluating the impact on fuel consumption of vehicle speed, close-following between vehicles, and lifting trailer axles on unloaded B-trains. Other tests targeted comparisons between trans-container road-trains and van semi-trailers road-trains, between curtain-sided semi-trailers, trans-containers and van semi-trailers, and between tractors pulling logging semi-trailers loaded with tree-length wood and short wood. The impact of a heavy-duty bumper on fuel consumption and the influence of B5 biodiesel blend on fuel consumption were also assessed.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Diesel Particulate Filters (DPF) are a key component in many on- and off-road aftertreatment systems to meet increasingly stringent particle emissions limits. Efficient thermal management and regeneration control is critical for reliable and cost-effective operation of the combined engine and aftertreatment system. Conventional DPF control systems predominantly rely on a combination of filter pressure drop measurements and predictive models to indirectly estimate the soot loading state of the filter. Over time, the build-up of incombustible ash, primarily derived from metal-containing lubricant additives, accumulates in the filter to levels far exceeding the DPF's soot storage limit. The combined effects of soot and ash build-up dynamically impact the filter's pressure drop response, service life, and fuel consumption, and must be accurately accounted for in order to optimize engine and aftertreatment system performance.

The objective of this project was to compare the fuel consumption and traction performances of 6 × 2 and 6 × 4 Class 8 tractors. Two approaches have been considered: evaluation of 6 × 2 tractors, modified from 6 × 4 tractors, and evaluation of OEM 6 × 2 tractors. Compared to the 6 × 4 tractors, which are equipped with a rear tandem with both drive axles, the 6 × 2 tractors have a rear tandem axle with one drive axle, and one non-drive axle, also called dead axle. The 6 × 2 tractor configurations are available from the majority of Class 8 tractor manufacturers. The SAE Fuel Consumption Test Procedures Type II (J1321) and Type III (J1526) were used for fuel consumption track test evaluations. Traction performances were assessed using pull sled tests to compare pulling distance, maximum speed, and acceleration when pulling the same set sled on similar surface.

Comparison studies have been conducted on a 1:16th scale model and a full scale tractor trailer of a variety of sealed aft cavity devices as a means to develop or enhance commercial drag reduction technology for class 8 vehicles. Various base cavity geometries with pressure taps were created for the scale model. The studies confirmed that length has an important effect on performance. The interaction of the boat-tailed aft cavity with other drag reduction devices, specifically side skirts, was investigated with results showing no discernable drag performance interaction between them. Overall, the experiments show that a boat-tailed aft cavity can reduce the drag up to 13%. Full-scale tests of a commercially derived product based on these scale tests were also completed using SAE Type II testing procedures. Full-scale tests indicated a fuel savings of over 6.5%.

Implementation of EPA's heavy-duty engine NOx standard of 0.20 g/bhp-hr has resulted in the introduction of a new generation of emission control systems for on-highway heavy-duty diesel engines. These new control systems are predominantly based around aftertreatment systems utilizing urea-based selective catalytic reduction (SCR) techniques, with only one manufacturer relying solely on in-cylinder NOx emission reduction techniques. As with any new technology, EPA is interested in evaluating whether these systems are delivering the expected emissions reductions under real-world conditions and where areas for improvement may lie. To accomplish these goals, an in-situ gaseous emissions measurement study was conducted using portable emissions measurement devices. The first stage of this study, and subject of this paper, focused on engines typically used in line-haul trucking applications (12-15L displacement).

Researches for automated construction machinery have been conducted for labor-saving, improved work efficiency and worker's safety, where a tracking control function was proposed as one of the key control system strategies for highly automated productive hydraulic excavators. An optimized digging trajectory that assures as much soils scooped as possible and less energy consumption is critical for an automated hydraulic excavator to improve work efficiency. Simulation models that we used to seek an optimized digging trajectory in this study consist of soil models and front linkage models of a hydraulic excavator. We developed two types of soil models. One is called wedge models used to calculate reaction forces from soils acting on a bucket during digging operation, based on the earth pressure theory. The other is called Distinct Element Method (DEM) model used to analyze soil behaviors and estimate amounts of soils scooped and reaction forces quantitatively.

The incorporation of hydrogen fuel cells into heavy duty tactical mobility vehicles can bring about great opportunities in reducing the pollutant emissions of this kind of platforms (GVW > 30,000 kg). Furthermore the transportation of fuel to operational areas has become a key aspect for any deployment therefore optimal use of this resource is of paramount importance. Finally, it is also quite common for such platforms to serve additional purposes, besides freight delivery, such as powering external equipment (i.e. field hospitals or mobile artillery pieces). This work will describe the intelligent energy management system for a PEM Fuel Cell-Battery-Ultracapacitor Hybrid 8×8 heavy truck of the aforementioned weight class which also contemplates an internal electric/traction power generation unit. It will describe how the system optimizes the use of battery and hydrogen fuel energy while keeping system efficiency and performance at a maximum.

Electric vehicles have a limitation of limited range and long charging time. Energy optimization plays a very crucial role in determining the range of an electric vehicle. The innovative system proposed here gives the opportunity to reduce energy wastage and efficiently direct the electrical energy to improve the driving range of a 9 meter AC electric bus. The high voltage air conditioner unit alone consumes more than 40% of the electrical energy stored in the traction battery which reduces the driving range of the electric bus drastically. The proposed system optimizes the air conditioner utilization to direct cool air only in areas where passengers are present. Buses do not always run on full capacity, when there are less number of people in the bus the system detects the locations of the passengers using sensors and occupant detection algorithm, this enables the controller to identify the areas where cooling has to be focused and where cooling can be reduced or stopped.