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Advanced Driver Assistance Systems (ADAS) are becoming common on passenger cars and pickup trucks. Accordingly, the manufacturers and installers of aftermarket equipment for these vehicles have an interest in confirming the functionality of ADAS when their equipment is put in place. However, there is very little publicly available information on the effect of aftermarket components on original equipment ADAS. To address this deficiency, a research program was undertaken in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations, including stock as well as three modified conditions. Aftermarket modifications to the vehicle consisted of increased tire diameters, a level kit, and two different lift kits. A series of physical tests were carried out to evaluate the ADAS performance of the vehicle with modifications.

Since the popularization of the Electric Vehicle (EV) there has been a large movement of consumers, governments, and the automotive industry due to its environmentally friendly characteristics. Unlike an IC engine, the batteries use multitudes of rare earth minerals and complex manufacturing processes which in some cases have been shown to produce as many emissions as an ICE vehicle over its entire lifespan. Another unnoticed important environmental concern has been the final recycling and disposal of the power train after its use. Unlike an ICE engine, which can be melted down or re-used, recycling batteries are much more difficult. In most cases the recycling process and the byproducts produced can be very harmful to the environment. This paper aims to be a complete cradle-to-grave analysis of all emissions produced in the life of an EV battery.

As automated driving becomes more common, simulation of vehicle dynamics and control scenarios are increasingly important for investigating motion control approaches. In this work, a study of the differences between the Pure Pursuit and Stanley autonomous vehicle controllers, based on vehicle dynamics responses, is presented. Both are geometric controllers that use only immediate vehicle states, along with waypoint data, to control a vehicle’s future direction as it proceeds from point to point, and both are among the most popular lateral controllers in use today. The MATLAB Automated Driving Toolbox is employed to implement and virtually test the Pure Pursuit and Stanley lateral controllers in different driving scenarios. These include low intensity scenarios such as city driving, and emergency maneuvers such as the moose test.

Forward collision warning is one of the most challenging concerns in the safety of autonomous vehicles. A cooperation between many sensors such as LIDAR, Radar and camera helps to enhance the safety. Apart from the importance of having a reliable object detector, the safety system should have requisite capabilities to make reasonable decisions in the moment. In this work, we concentrate on detecting front vehicles of autonomous cars using a monocular camera, beyond only a detection method. In fact, we devise a solution based on a cooperation between a deep object detector and a reinforcement learning method to provide forward collision warning signals. The proposed method models the relation between acceleration, distance and collision point using the area of the bounding box related to the front vehicle. An agent of learning automata as a reinforcement learning method interacts with the environment to learn how to behave in eclectic hazardous situations.

As advanced vehicle controls and autonomy become mainstream in the automotive industry, the need to employ traditional mathematical models and control strategies arises for the purpose of simulating autonomous vehicle handling maneuvers. This study focuses on lane change maneuvers for autonomous vehicles driving at low speeds. The lane change methodology uses PID (Proportional-Integral-Derivative) controller to command the steering wheel angle, based on the yaw motion and lateral displacement of the vehicle. The controller was developed and tested on a bicycle model of an electric vehicle (a Chevrolet Bolt 2017), with the implementation done in MATLAB/Simulink. This simple mathematical model was chosen in order to limit computational demands, while still being capable of simulating a smooth lane change maneuver under the direction of the car’s mission planning module at modest levels of lateral acceleration.

Rapid changes in the automotive industry, including the growth of advanced vehicle controls and autonomy, are driving the need for more dedicated proving ground spaces where these systems can be developed safely. To address this need, Kettering University has created the GM Mobility Research Center, a 21-acre proving ground located in Flint, Michigan at the former “Chevy in the Hole” factory location. Construction of a proving ground on this site represents a beneficial redevelopment of an industrial brownfield, as well as a significant expansion of the test facilities available at the campus of Kettering University. Test facilities on the site include a road course and a test pad, along with a building that has garage space, a conference room, and an indoor observation platform. All of these facilities are available to the students and faculty of Kettering University, along with their industrial partners, for the purpose of engaging in advanced transportation research and education.

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire.

The safety of ground vehicles is a matter of critical importance. Vehicle safety is enhanced with the use of control systems that mitigate the effect of unachievable demands from the driver, especially demands for tire forces that cannot be developed. This paper presents the results of a smart tire prototyping and validation study, which is an investigation of a smart tire system that can be used as part of these mitigation efforts. The smart tire can monitor itself using in-tire sensors and provide information regarding its own tire forces and moments, which can be transmitted to a vehicle control system for improved safety. The smart tire is designed to estimate the three orthogonal tire forces and the tire aligning moment at least once per wheel revolution during all modes of vehicle operation, with high accuracy. The prototype includes two in-tire piezoelectric deformation sensors and a rotary encoder.

With the recent advances in rapid modeling and rapid prototyping, accurate simulation models for tires are very desirable. Selection of a tire slip model depends on the required frequency range and nonlinearity associated with the dynamics of the vehicle. This paper presents a brief overview of three major slip concepts including “Stationary slip”, “Physical transient slip”, and “Pragmatic transient slip”; tire models use these slip concepts to incorporate tire slip behavior. The review illustrates that there can be no single accurate slip model which could be ideally used for all modes of vehicle dynamics simulations. For this study, a rigid ring based semi-analytical tire model for intermediate frequency (up to 100 Hz) is used.

Vehicles are in contact with the road surface through tires, and the interaction at the tire-road interface is usually the major source of vibrations that is experienced by the passengers in the vehicle. Thus, it is critical to measure the vibrational characteristics of the tires in order to improve the safety and comfort of the passengers and also to make the vehicle quieter. The measurement results can also be used to validate numerical models. In this paper, Digital Image Correlation (DIC) as a non-contact technique is used to measure the dynamics of a racing tire in static and rolling conditions. The Kettering University FSAE car is placed on the dynamometer machine for this experiment. A pair of high-speed cameras is used to capture high-resolution images of the tire in a close-up view. The images are processed using DIC to obtain strain and displacement of the sidewall of the tire during rolling. The experiment is performed for various testing speeds.

This paper documents the electrical infrastructure design of a Hybrid Go Kart competition vehicle which includes a dual Fuel Cell power system, Ultra Capacitors for energy storage, and a dual AC induction motor capable of independent drive. The Kart was built primarily to compete in the 2009 Formula Zero international event. This paper emphasized the vehicle model and control strategy as a result of three (3) graduate student research projects. The vehicle was fabricated and tested but did not participate in the race competition since the race organization folded. The vehicle model was developed in Simulink to determine whether the fuel cell and ultra-capacitor combination will be sufficient for peak transient power requirement of 14 kW. The vehicle’s functional description and performance specifications are documented including the integration of the fuel cell power modules, energy storage system, power converters, and AC motor and motor controllers.

Most of the present EV on-board chargers utilize a three-stage design, e.g., AC/DC rectifier, DC to high-frequency AC inverter, and AC to DC rectifier, which limits the wall-to-battery efficiency to ∼94%. To further increase the efficiency and power density, a matrix converter is an excellent candidate directly converting grid AC to high-frequency AC thereby saves one stage. However, its control complexity and the high cost of building the back-to-back switches are barriers its acceptance. Instead, this paper adopts the 650V E-mode GaN HEMTs to build a level-2 on-board charger using the indirect matrix topology. The input voltage is 80∼260VAC, the battery voltage is 200∼500VDC and the rated power is 7.2kW. Variable switching frequency is combined with phase-shift control to realize the zero-voltage switching. To further increase the system efficiency, four GaN HEMTs are paralleled to form one switching module with a novel gate-drive technology.

Typically, when someone needs to perform occasional towing tasks, such as towing a boat on a trailer, they have two choices. They can either purchase a larger, more powerful vehicle than they require for their regular usage, or they can rent a larger vehicle when they need to tow something. In this project, we propose a third alternative: a trailer with an on-board power supply, which can be towed by a small vehicle. This system requires a means of sensing how much power the trailer's power supply should provide, and an appropriate control system to provide this power. In this project, we design and model the trailer, a standard small car, and the control system, and evaluate the concept's feasibility. We have selected a suitable power source for the trailer, a DC motor, coupled directly to the trailer's single drive wheel, which allow us to dispense with the need for a differential.

Lean applications in product development usually start with manufacturing due to the relative experience of measuring improvements and identifying wastes in physical settings. The full potential of lean implementation in any product development, however, can only be realized when applied throughout the process, starting with early process. Considering that the first and most essential principle in lean implementation is the characterization of value from the customer's perspective, it is imperative that the proper definition of value is realized at the beginning of the process. In addition, streaming and flowing of this customer's specified value should be realized throughout the process from start to finish. This paper discusses the application of lean principles to integrated design and manufacturing phases of the Product Development Process.

Steer-by-wire is a system where there are no mechanical connections between the steering wheel and the tires. With the inception of electric and hybrid cars, steer-by-wire is becoming more common. A steer-by-wire car opens many opportunities for additional feedback on the steering wheel. Providing haptic feedback through the steering wheel will add additional depth and capabilities to make the driving experience safer. In this paper we investigated the effects of force feedback on the steering wheel in order to detect and/or avoid blind spot collisions. Two types of force feedback are examined using a driving simulator: a rumble and a counter steering force. A rumble on the steering wheel can avoid blind-spot accidents by providing feedback to drivers about vehicles in their blind spots. Providing counter steering force feedback can help in the reduction in blind-spot accidents. The results show that adding counter steering force feedback did reduce blind-spot related collisions.

The objective of this study was to determine risk of injury to the driver during a frontal impact in a Formula SAE vehicle. Formula SAE is a collegiate student design competition where every year universities worldwide build and compete with open-wheel formula-style race cars. Formula SAE 2006 rules stipulate the use of an impact attenuator to absorb energy in the event of a frontal impact. These rules mandated an average deceleration not to exceed 20-g from a speed of 7.0 m/s (23 ft/s), but do not specify a specific time or pulse shape of the deceleration. The pulse shapes tested in this study included an early high-g, constant-g, and late high-g pulse. The tests were performed using the deceleration sled at the Kettering University Crash Safety Center. Using industry standard practices, this study examined the driver's risk of injury with regard to neck and femur loads, head and chest accelerations, as well as kinematic analysis using high speed video.

The “Range-of Motion of the Cervical Spine of Children” study is a collaboration between Kettering University and McLaren Regional Medical Center in Flint, Michigan to quantify and establish benchmarks of “normal” range of motion (ROM) in children. The results will be analyzed to determine mean and standard deviation of degrees of rotation and used to improve the occupant protection in motor vehicles, sports equipment and benefits of physical therapy. The data will be invaluable in the development of computational models to analyze processes involving children in motion.

The application of DO-178B for the verification and validation of the safety-critical aspects of a steer-by-wire sub-system of a vehicle by using a spiral development model is discussed. The project was performed within a capstone design course at Kettering University. Issues including lessons learned regarding requirements, specifications, testing, verification, and validation activities as required by DO-178B are summarized.

A hardware and software architecture suitable for a safety-critical steer-by-wire systems is presented. The architecture supports three major failure modes and features several safety protocols and mechanisms. Failures due to component failures, software errors, and human errors are handled by the architecture and safety protocols. A test implementation using replicated communication channels, controllers, sensors, and actuators has been performed. The test implementation uses the CAN protocol, Motorola S12 microcontrollers, and Microchip MCP250XX components with a steering wheel and road wheel simulator. The focus of the paper is on the application level, using system engineering principles which incorporate a holistic approach to achieve safety at various levels.

This paper describes the experiments conducted to determine the effect of high energy multiple spark discharge (MSD) ignition systems and spark plug electrode design, on the cold start performance of a vehicle which was converted for dedicated operation on E85 (a blend of 85% ethanol and 15% gasoline) fuel. Tests were conducted using three different ignition configurations; original equipment manufacturer (OEM) ignition and spark plugs, high energy multiple spark discharge (MSD) ignition with OEM, J-type spark plugs, and high energy MSD ignition with surface gap electrode spark plugs. The high energy MSD ignition with OEM spark plugs showed a significant improvement in cold start performance over the OEM ignition. The addition of the surface gap spark plugs caused a decrease in cold start performance. Despite this, the surface gap spark plugs produced higher ending coolant temperature than the other configurations.