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As vehicles with SAE level 2 of autonomy become more widely deployed, they still rely on the human driver to monitor the driving task and take control during emergencies. It is therefore necessary to examine the Human Factors affecting a driver’s ability to recognize and execute a steering or pedal action in response to a dangerous situation when the autonomous system abruptly requests human intervention. This research used a driving simulator to introduce the concept of level 2 autonomy to a cohort of 60 drivers (male: 48%, female: 52%) of different age groups (teens 16 to 19: 32%, adults: 35 to 54: 37%, seniors 65+: 32%). Participants were surveyed for their perspectives on self-driving vehicles. They were then assessed on a driving simulator that mimicked SAE level 2 of autonomy. Participants’ interaction with the HMI was studied.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

Sustained NOx reduction at low temperatures, especially in the 150-200 °C range, shares some similarities with the more commonly discussed cold-start challenge, however, poses a number of additional and distinct technical problems. In this project, we set a bold target of achieving and maintaining 90% NOx conversion at the SCR catalyst inlet temperature of 150 °C. This project is intended to push the boundaries of the existing technologies, while staying within the realm of realistic future practical implementation. In order to meet the resulting challenges at the levels of catalyst fundamentals, system components, and system integration, Cummins has partnered with the DOE, Johnson Matthey, and Pacific Northwest National Lab and initiated the Sustained Low-Temperature NOx Reduction program at the beginning of 2015 and completed in 2017.

NVH development of light duty diesel engines require significant collaboration with the OEM as compared to medium duty and heavy duty diesel engines. Typically, competitive benchmark studies and customer expectations define the NVH targets at the vehicle level and are subsequently cascaded down to the powertrain level. For engine manufacturing companies like Cummins Inc., it is imperative to work closely with OEM to deliver on the NVH expectations. In certain situations, engine level NVH targets needs to be demonstrated in the OEM or 3rd party acoustic test facility for customer satisfaction or commercial purposes. Engine noise tests across different noise test facilities may introduce some variation due to differences in the acoustic test facilities, test hardware, instrumentation differences, etc. In addition, the engine itself is a major source of variation.

Most of the history of systems engineering has been focused on processes for engineering a single complex system. However, most large enterprises design, manufacture, operate, sell, or support not one product but multiple product lines of related but varying systems. They seek to optimize time to market, costs of development and production, leverage of intellectual assets, best use of talented human resources, overall competitiveness, overall profitability and productivity. Optimizing globally across multiple product lines does not follow from treating each system family member as an independently engineered system or product. Traditional systems engineering principles can be generalized to apply to families. This article includes a multi-year case study of the actual use of a generic model-based systems engineering methodology for families, Systematica™, across the embedded electronic systems products of one of the world's largest manufacturers of heavy equipment.

The focus of this paper is to discuss the modeling and control of intake plenum pressure on the Powertrain Control Research Laboratory's (PCRL) Single-Cylinder Engine (SCE) transient test system using a patented device known as the Intake Air Simulator (IAS), which dynamically controls the intake plenum pressure, and, subsequently, the instantaneous airflow into the cylinder. The IAS exists as just one of many devices that the PCRL uses to control the dynamic boundary conditions of its SCE transient test system to make it “think” and operate as though it were part of a Multi-Cylinder Engine (MCE) test system. The model described in this paper will be used to design a second generation of this device that utilizes both continuously and discretely actuating valves working in parallel.

The SAE AutoDrive Challenge II is a four-year collegiate competition dedicated to developing a Level 4 autonomous vehicle by 2025. In January 2023, the participating teams each received a Chevy Bolt EUV. Within a span of five months, the second phase of the competition took place in Ann Arbor, MI. The authors of this contribution, who participated in this event as team Wisconsin Autonomous representing the University of Wisconsin–Madison, secured second place in static events and third place in dynamic events. This has been accomplished by reducing reliance on the actual vehicle platform and instead leveraging physical analogs and simulation. This paper outlines the software and hardware infrastructure of the competing vehicle, touching on issues pertaining sensors, hardware, and the software architecture employed on the autonomous vehicle. We discuss the LiDAR-camera fusion approach for object detection and the three-tier route planning and following systems.

Powertrain simulation is becoming an increasingly valuable tool to evaluate new technologies proposed for future military vehicles. The powertrain of the M1A1 Abrams tank is currently being modeled in the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison. This powertrain model is to be integrated with other component models in an effort to produce a high fidelity simulation of the entire vehicle.

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.

During the early 1990s, the Track-Type Tractors Division (TTTD) of Caterpillar Inc. experienced several challenges. The Division faced increasing global competition in the midst of an economic recession. Although intense plant modernization and reorganization occurred in the five previous years, the business unit was not profitable. In 1993, Track-Type Tractors Division instituted its solution -- a change in its culture. Previously, the culture hindered the division’s ability to move forward. This was revealed in a 1992 review detailing the major obstacles inhibiting management from achieving divisional goals. The division leaders recognized that a change in business philosophy, as opposed to further plant modernization, was required to achieve production goals and stay globally competitive.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. Presenter Nagesh Belludi, Cummins Inc.

This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. We have subsequently extended this VMS architecture to build a grid-computing platform to support high volume of simulation needs. The building block of the grid-computing version of VMS is an executable file that consists of vehicle and engine simulation models compiled using Real Time Workshop. This executable file integrates MATLAB and Simulink with Java, XML, and JDBC technologies and interacts with the MySQL database. Our grid consists of a cluster of twenty Linux servers with quad-core processors. The Sun Grid Engine software suite that administers this cluster can batch-queue and execute 80 simulations concurrently.

The automotive industry drives some of the most stringent product requirements to ensure long product life and customer satisfaction. To demonstrate compliance with these requirements new and more accurate evaluation methods are needed. Thermal fatigue life in EGR coolers for heavy duty diesel applications have historically been a critical focus for engine OEMs. Being able to accurately evaluate product return rates due to thermal fatigue failures gives the OEM confidence that all end users will be satisfied, and allows program management to properly make fiscal decisions. Additionally, weight and cost optimization can be conducted with greater confidence. This is accomplished by accounting for product variation and application variation in thermal fatigue life evaluations. Including these variations requires a simplified numerical method to calculate product life, as tens of thousands of samples will be run through the analysis to represent real life random variation.

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer.

This paper presents the business purpose, software architecture, technology integration, and applications of the Cummins Vehicle Mission Simulation (VMS) software. VMS is the value-based analysis tool used by the marketing, sales, and product engineering functions to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. VMS leverages the best of software architecture practices and proven technologies available today. It consists of a close integration of MATLAB and Simulink with Java, XML, and JDBC technologies. This Windows compatible application software uses stand-alone mathematical models compiled using Real Time Workshop. A built-in MySQL database contains product data for engines, driveline components, vehicles, and topographic routes. This paper outlines the database governance model that facilitates effective management, control, and distribution of engine and vehicle data across the enterprise.

This paper identifies potential performance benefits and computational costs of applying advanced multivariable control theory concepts to coordinate the control of a general multi-degree-of-freedom fuel system. The control variables are injection duration and pressure. The focus is on the design of a robust multi-input multi-output controller using H-infinity and mu synthesis methodology to coordinate the control of injection duration and pressure; reduce overshoots and system sensitivity to parameter variations caused by component aging. Model reduction techniques are used to reduce the order of the H-infinity controller to make it practically implementable. Computer simulation is used to test the robust performance of a generic engine and fuel system model controlled by the reduced order H-infinity controller and a traditional proportional plus integral controller.

The interest for NOx estimators (also known as virtual sensors or inferential sensors) has increased over the recent years due to benefits attributed to cost and performance. NOx estimators are typically installed to improve On-Board Diagnostics (OBD) monitors or to lower bill of material costs by replacing physical NOx sensors. This paper presents initial development results of a virtual engine-out NOx estimator planned for the implementation on an ECM. The presented estimator consists of an airpath observer and a NOx combustion model. The role of the airpath observer is to provide input values for the NOx combustion model such as the states of the gas at the intake and exhaust manifolds. It contains a nonlinear mean-value model of the airpath suitably transformed for an efficient and robust implementation on an ECM. The airpath model uses available sensory information in the vehicle to correct predictions of the gas states.

Today’s business climate and economy demand new, innovative strategies from the initial kickoff of research and development - to the mining of ore from the earth - to the final inspection of a finished product in a mid-western factory. From startup companies with two employees to the largest companies, the world faces new and challenging requirements every day. The demands from companies, customers, executives, and shareholders continue to drive for higher outputs with more efficient use of personnel and investments. Fortunately, the rate of technology continues to exponentially accelerate, which allows those at the cutting edge of technology to capitalize. Caterpillar has been a pioneer in advanced technology since its inception and has been developing the foundation for autonomy over the past four decades.

Most pieces of mobile equipment (machines) produce an audible signal to indicate movement in the rearward direction. This signal is intended to alert nearby personnel of the potential danger associated with the machine moving in a direction where the operator may not be able to see people or objects in the machine path. Anyone who has been on or near a construction site recognizes the familiar “beep…beep…beep…” of this signal as the backup alarm. To be effective, the backup alarm must be discernible, timely, and relevant to those people where a reaction is intended. As machine designers respond to various sound directives for reducing sound emissions (including the backup alarm), the performance of the backup alarm is receiving special attention. An emerging solution is an alarm capable of sensing ambient sounds and producing an audible signal proportional to the sensed sound levels-a self-adjusting backup alarm.