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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.

This article analyzes the aerodynamic performance of Class 8 tractor-trailer geometries made available by the Environmental Protection Agency (EPA) using CFD simulation. Large Eddy Simulations (LES) were carried out with the CFD package, Simerics-MP+. A Sleeper tractor and a 53-foot box trailer configuration was considered. The configuration featured a detailed underbody, an open-grille under-hood engine compartment, mirrors, and the radiator and condenser. Multiple tractor-trailer variants were studied by adding aerodynamic surfaces to the baseline geometries. These include tank fairings and side extenders for the cabins, two types of trailer skirts, and a trailer tail. The effect of these devices towards reducing the overall vehicle drag was investigated. Mesh generation was carried out directly on the given geometry, without any surface modifications, using Simerics’ Binary-Tree unstructured mesher.

Eco-driving algorithms enabled by Vehicle to Everything (V2X) communications in Connected and Automated Vehicles (CAVs) can improve fuel economy by generating an energy-efficient velocity trajectory for vehicles to follow in real time. Southwest Research Institute (SwRI) demonstrated a 7% reduction in energy consumption for fully loaded class 8 trucks using SwRI’s eco-driving algorithms. However, the impact of these schemes on vehicle emissions is not well understood. This paper details the effort of using data from SwRI’s on-road vehicle tests to measure and evaluate how eco-driving could impact emissions. Two engine and aftertreatment configurations were evaluated: a production system that meets current NOX standards and a system with advanced aftertreatment and engine technologies designed to meet low NOX 2031+ emissions standards.

Despite considerable progress towards clean air in previous decades, parts of the United States continue to struggle with the challenge of meeting the ambient air quality targets for smog-forming ozone mandated by the U.S. EPA, with some of the most significant challenges being seen in California. These continuing issues have highlighted the need for further reductions in emissions of NOX, which is a precursor for ozone formation, from a number of key sectors including the commercial vehicle sector. In response, the California Air Resources Board (CARB) embarked on a regulatory effort culminating in the adoption of the California Heavy-Duty Low NOX Omnibus regulation.[1] This regulatory effort was supported by a series of technical programs conducted at Southwest Research Institute (SwRI).

Vehicle to Everything (V2X) communication has enabled on-board access to information from other vehicles and infrastructure. This information, traditionally used for safety applications, is increasingly being used for improving vehicle fuel economy [1-5]. This work aims to demonstrate energy consumption reductions in heavy/medium duty vehicles using an eco-driving algorithm. The algorithm is enabled by V2X communication and uses data contained in Basic Safety Messages (BSMs) and Signal Phase and Timing (SPaT) to generate an energy-efficient velocity trajectory for the vehicle to follow. An urban corridor was modeled in a microscopic traffic simulation package and was calibrated to match real-world traffic conditions. A nominal reduction of 7% in energy consumption and 6% in trip time was observed in simulations of eco-driving trucks.

Safety, fuel economy and uptime are key requirements for the operation of heavy-duty line-haul trucks within a fleet. With the penetration of connectivity and automation technologies, energy optimal and safe operation of the trucks are further improved through Advanced Driver Assistance System (ADAS) features and automated technologies as in truck platooning. Understanding the braking capability of the vehicle is very important for optimal ADAS and platooning control system design and integration. In this paper, the importance of tire connectivity and tire conditions on truck stopping distance are demonstrated through testing. The test data is further utilized to develop tire models for integration in an optimal vehicle automation for platooning. New ways to produce and use the tire related information in real-time optimal control of platooning trucks are proposed and the contribution of tire information in fuel economy is quantified through simulations.

Current industry trends in both powertrain electrification and vehicle drag reduction point towards reduced peak and average power demands from the internal combustion engine in future long-haul class 8 vehicles. Downsizing the engine displacement to match these new performance requirements can yield a benefit in drive cycle efficiency through reduced friction and improved cruise load efficiency. Downsizing by reducing cylinder count avoids the heat loss and friction penalties from reduced per-cylinder displacement and could allow a manufacturer to continue to leverage the highly optimized combustion system from existing heavy-duty engines in the new downsized offering. The concept of this study is to leverage powertrain electrification and the improvement trends in vehicle aerodynamics and rolling resistance to develop a fuel economy focused, downsized heavy duty diesel powertrain for future long-haul vehicles utilizing a reduced cylinder count.

Evaluation of the platooning legislative space suggests a limited near-term opportunity for autonomous vehicles as currently only nine states have platooning and autonomous favorable legislations. An extensive closed-loop vehicle model simulation was conducted to quantify two-truck platooning fuel economy entitlement benefits across all United States (US) interstate routes (I-xx) spanning over 40,000 miles as compared to a single truck. A simultaneous study was carried out to identify the density of Class 8 heavy-duty trucks on these interstates, using the Freight Analysis Framework (FAF) 4 database. These two studies were combined to ascertain interstates that foresee the least fuel consumption due to platooning and thus identifying states with the most platooning benefits. Identification of states with most platooning benefits provides realistic data to push for autonomous driving and platooning legislations.

Range-extended hybrids are an attractive option for medium- and heavy-duty commercial vehicle fleets because they offer the efficiency of an electrified powertrain with the driving range of a conventional diesel powertrain. The vehicle essentially operates as if it was purely electric for most trips, while ensuring that all commercial routes can be completed in any weather conditions or geographic terrain. Fuel use and point-source emissions can be significantly reduced, and in some cases eliminated, as many shorter routes can be fully electrified with this architecture. Under a U.S. Department of Energy (DOE)-funded project for Medium- and Heavy-Duty Vehicle Powertrain Electrification, Cummins has developed a plug-in hybrid electric Class 6 truck with a range-extending engine designed for pickup and delivery application.

Fuel usage negatively impacts the environment and is a significant portion of operational costs of moving freight globally. Reducing fuel consumption is key to lessening environmental impacts and maximizing freight efficiency, thereby increasing the profit margin of logistic operators. In this paper, fuel economy improvements of a cab-over style 49T heavy duty Foton truck powered by a Cummins 12-liter engine are studied and systematically applied for the China market. Most fuel efficiency improvements are found within the vehicle design when compared to opportunities available at the engine level. Vehicle design (improved aerodynamics), component selection/matching (low rolling resistance tires), and powertrain electronic features integration (shift schedule/electronic trim) offer the largest opportunities for lowering fuel consumption.

Cummins has recently launched next-generation aftertreatment technology, the Single ModuleTM aftertreatment system, for medium-duty and heavy-duty engines used in on-highway and off-highway applications. Besides meeting EPA 2010+ and Euro VI regulations, the Single ModuleTM aftertreatment system offers 60% volume and 40% weight reductions compared to current aftertreatment systems. In this work, we present model-based approaches that were systematically adopted in the design and development of the Cummins Single ModuleTM aftertreatment system. Particularly, a variety of analytical and experimental component-level and system-level validation tools have been used to optimize DOC, DPF, SCR/ASC, as well as the DEF decomposition device.

Countries around the world are expected to continue to adopt more stringent emissions standards for heavy-duty markets for both oxides of nitrogen (NOx) and greenhouse gases (GHG). While there is uncertainty about the timing and extent of these regulations, it is clear that significant reductions will be required to address urban air pollution and climate change concerns. The rate and pace of technology evolution and how it will affect the energy pathways for commercial transportation and industrial use are dependent on multiple variables such as national energy and environmental policies and public-private partnerships. Although it adds complexity, the engine system has great potential to evolve as it continues to be highly integrated into the super system for which it is producing power. This paper examines the potential opportunities and challenges for engine manufacturers to continue to be the supplier of power to vehicles and equipment of the future.

Actuators are the key to allowing machines to become more sophisticated and perform complex tasks that were previously done by humans, providing motion in a safe, controlled manner. As defined in this book, actuator design is a subset of mechanical design. It involves engineering the mechanical components necessary to make a product move as desired. Fundamentals of Engineering High-Performance Actuator Systems, by Ken Hummel, was written as a text to supplement actuator design courses, and a reference to engineers involved in the design of high-performance actuator systems. It highlights the design approach and features what should be considered when moving a payload at precision levels and/or speeds that are not as important in low-performance applications.

While initial Connected Vehicle research in the United States was focusing almost exclusively on passenger vehicles, a program was envisioned that would enhance highway safety, mobility, and operational efficiencies through the application of the technology to commercial vehicles. This program was realized in 2009 by funding from the I-95 Corridor Coalition, led by the New York State Department of Transportation, and called the Commercial Vehicle Infrastructure Integration (CVII) program. The CVII program focuses on developing, testing and deploying Connected Vehicle technology for heavy vehicles. Since its inception, the CVII program has developed numerous Vehicle-to-Vehicle and Vehicle-to-Infrastructure applications for trucks that leverage communication with roadside infrastructure and other light and heavy duty vehicles to meet the objectives of the program.

Since the turn of the millennium, automated vehicle technology has matured at an exponential rate, evolving from research largely funded and motivated by military and agricultural needs to a near-production market focused on everyday driving on public roads. Research and development has been conducted by a variety of entities ranging from universities to automotive manufacturers to technology firms demonstrating capabilities in both highway and urban environments. While this technology continues to show promise, corner cases, or situations outside the average driving environment, have emerged highlighting scenarios that impede the realization of full automation anywhere, anytime. This paper will review several of these corner cases and research deficiencies that need to be addressed for automated driving systems to be broadly deployed and trusted.

Various 1D simulation tools (KULI & LMS Amesim) and 3D simulation tools (ANSYS FLUENT®) can be used to size and evaluate truck cooling system design. In this paper, ANSYS FLUENT is used to analyze and validate the design of medium duty truck cooling systems. LMS Amesim is used to verify the quality of heat exchanger input data. This paper discusses design and simulation of parent and derivative trucks. As a first step, the parent truck was modeled in FLUENT (using standard' k - ε model) with detailed fan and underhood geometry. The fan is modeled using Multiple Reference Frame (MRF) method. Detailed geometry of heat exchangers is skipped. The heat exchangers are represented by regular shape cell zones with porous medium and dual cell heat exchanger models to account for their contributions to the entire system in both flow and temperature distribution. Good agreement is observed between numerical and experimental engine out temperatures at different engine operating conditions.

This paper describes the potential for the use of Dedicated EGR® (D-EGR®) in a gasoline powered medium truck engine. The project goal was to determine if it is possible to match the thermal efficiency of a medium-duty diesel engine in Class 4 to Class 7 truck operations. The project evaluated a range of parameters for a D-EGR engine, including displacement, operating speed range, boosting systems, and BMEP levels. The engine simulation was done in GT-POWER, guided by experimental experience with smaller size D-EGR engines. The resulting engine fuel consumption maps were applied to two vehicle models, which ran over a range of 8 duty cycles at 3 payloads. This allowed a thorough evaluation of how D-EGR and conventional gasoline engines compare in fuel consumption and thermal efficiency to a diesel. The project results show that D-EGR gasoline engines can compete with medium duty diesel engines in terms of both thermal efficiency and GHG emissions.

This paper presents the fuel consumption results of engine and vehicle simulation modeling for a wide variety of individual technologies and technology packages applied to a long haul heavy duty vehicle. Based on the simulation modeling, up to 11% in fuel savings is possible using commercially available and emerging technologies applied to a 15L DD15 engine alone. The predicted fuel savings are up to 17% in a Kenworth T700 tractor-trailer unit equipped with a range of vehicle technologies, but using the baseline DD15 diesel engine. A combination of the most aggressive engine and vehicle technologies can provide savings of up to 29%, averaged over a range of drive cycles. Over 30% fuel savings were found with the most aggressive combination on a simulated long haul duty cycle. Note that not all of these technologies may prove to be cost-effective. The fuel savings benefits for individual technologies vary widely depending on the drive cycles and payload.

Simulations used to estimate carbon dioxide (CO2) emissions and fuel consumption of medium- and heavy-duty vehicles over prescribed drive cycles often employ engine fuel maps consisting of engine measurements at numerous steady-state operating conditions. However, simulating the engine in this way has limitations as engine controls become more complex, particularly when attempting to use steady-state measurements to represent transient operation. This paper explores an alternative approach to vehicle simulation that uses a “cycle average” engine map rather than a steady state engine fuel map. The map contains engine CO2 values measured on an engine dynamometer on cycles derived from vehicle drive cycles for a range of generic vehicles. A similar cycle average mapping approach is developed for a powertrain (engine and transmission) in order to show the specific CO2 improvements due to powertrain optimization that would not be recognized in other approaches.

Medium- and Heavy Duty Truck fuel consumption and the resulting greenhouse gas (GHG) emissions are significant contributors to overall U.S. GHG emissions. Forecasts of medium- and heavy-duty vehicle activity and fuel use predict increased use of freight transport will result in greatly increased GHG emissions in the coming decades. As a result, the National Highway Traffic Administration (NHTSA) and the United States Environmental Protection Agency (EPA) finalized a regulation requiring reductions in medium and heavy truck fuel consumption and GHGs beginning in 2014. The agencies are now proposing new regulations that will extend into the next decade, requiring additional fuel consumption and GHG emissions reductions. To support the development of future regulations, a research project was sponsored by NHTSA to look at technologies that could be used for compliance with future regulations.