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The Controller Area Network has become the standard of choice for most automotive manufacturers.  Approved for use as an ISO and EPA diagnostic network, its usage continues to grow.  This course covers the theory and use of the CAN protocol, and its applications in the automotive industry.  Details on how the CAN protocol and other standards (J2411, J2284, J1939, ISO 11898, etc.) complement each other will be presented. Participants will learn about CAN application layers; the latest J1939, J2284, J2411, and IDB standards, regulations, and implementation requirements; and details of device hardware and software interfaces.

Do you know what personal protective equipment (PPE), tools, and instruments are needed to keep you safe around high voltage (HV) vehicles? Are you aware of how to protect yourself or your employees when working around high voltage systems and platforms? Safety is paramount when working around any type of high voltage. As electric vehicles (EV) and EV fleets become more prevalent, the critical need for OEMs, suppliers, companies, and organizations to provide comprehensive safety training for teams working with or around xEV systems and platforms increases.

This paper compares two different rule-based power management (PM) strategies, in terms of their resultant fuel consumptions, through a simulation study as applied to a hybrid hydraulic multi-actuator displacement controlled (DC) system. Presenter Rohit Hippalgaonkar

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.

Advanced vehicular thermal management system can improve engine performance, minimize fuel consumption, and reduce emissions by harmoniously operating computer-controlled servomotor components. In this paper, a neural network-based optimal control strategy is proposed to regulate the engine temperature through the advanced cooling system. Presenter Asma Al Tamimi, Hashemite University

Concerned with fuel consumption and emissions, especially public transportation in urban areas, the ELFA electric drive system has been developed for hybrid bus applications. This modular system provides bus manufactures a cost effective solution with a maximum degree of design flexibility. Presenter Joshua Nelke, siemens industry inc.

Architecting and integrating commercial hybrid electric vehicles (HEV) is a long and labor intensive process which is unique every time. The challenge intensifies when one attempts to create an HEV capable of engine-off operation. Presenter Benjamin Saltsman, Eaton Corp.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. Presenter Chinmaya Patil, Eaton Corporation

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)

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 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 This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

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 The study of road loads on trucks plays a major role in assessing the effect of heavy-vehicle design on fuel conservation measures. Coastdown testing with full-scale vehicles in the field offers a good avenue to extract drag components, provided that random instrumentation faults and biased environmental conditions do not introduce errors into the results. However, full-scale coastdown testing is expensive, and environmental biases which are ever-present are difficult to control in the results reduction. Procedures introduced to overcome the shortcomings of full-scale field testing, such as wind tunnels and computational fluid dynamics (CFD), though very reliable, mainly focus on estimating the effects of aerodynamic drag forces to the neglect of other road loads which should be considered.

Abstract This article analyses the flow field between two 1/8-scale Generalized European Transport System (GETS) models which are placed in a two-vehicle platoon at close distances. Numerical simulations using the lattice Boltzmann method together with a wind tunnel experiment (open jet facility, OJF) were executed. Next, to balance measurements, coaxial volumetric velocimetry (CVV) measurements were performed to obtain information about the flow field. Three intervehicle distances, 0.10, 0.45 and 0.91 times the vehicle length, were tested for various platoon configurations where the vehicles in the platoon varied in terms of front-edge radius and the addition of tails. At the smallest intervehicle distance, the greatest reductions in drag were found for both the leading and trailing vehicles. The flow in the gap between the two vehicles follows an S-shaped path with small variations between the configurations.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

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.

A heavy truck wind tunnel test program is currently underway at the Langley Full Scale Tunnel (LFST). Seven passive drag reducing device configurations have been evaluated on a heavy truck model with the objective of understanding the practical limits to drag reduction achievable on a modern tractor trailer through add-on devices. The configurations tested include side skirts of varying length, a full gap seal, and tapered rear panels. All configurations were evaluated over a nominal 15 degree yaw sweep to establish wind averaged drag coefficients over a broad speed range using SAE J1252. The tests were conducted by first quantifying the benefit of each individual treatment and finally looking at the combined benefit of an ideal fully treated vehicle. Results show a maximum achievable gain in wind averaged drag coefficient (65 mph) of about 31 percent for the modern conventional-cab tractor-trailer.

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.

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.