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The automotive industry is currently experiencing a massive transformation, one like it has not quite seen in the past. With the advent of highly software-driven, always on, connected vehicles, the automotive industry is experiencing itself at a crossroads. While the traditional component-driven design approach to vehicle development worked in the favor of the industry for decades due to vehicles being mostly mechanical in nature, the industry now finds itself struggling to develop well-integrated vehicle solutions with the large dependency on software systems. The fast-paced nature of the software world makes it imperative to approach the development of automobiles from a Systems Engineering perspective. A function-based approach to the development of vehicle architectures can ensure cohesive systems development and a well-integrated vehicle.

Connectivity in ground vehicles allows vehicles to share crucial vehicle data, such as vehicle acceleration and speed, with each other. Using sensors such as radars and lidars, on the other hand, the intravehicular distance between a leader vehicle and a host vehicle can be detected. Cooperative Adaptive Cruise Control (CACC) builds upon ground vehicle connectivity and sensor information to form convoys with automated car following. CACC can also be used to improve fuel economy and mobility performance of vehicles in the said convoy. In this paper, a CACC system is presented, where the acceleration of the lead vehicle is used in the calculation of desired vehicle speed. In addition to the smooth car following abilities, the proposed CACC also has the capability to calculate a speed profile for the ego vehicle that is fuel efficient, making it an Ecological CACC (Eco-CACC) model.

This work represents an advanced engineering research project partially funded by the U.S. Department of Energy (DOE). Ford Motor Company, FEV North America, and Oak Ridge National Laboratory collaborated to develop a next generation boosted spark ignited engine concept. The project goals, specified by the DOE, were 23% improved fuel economy and 15% reduced weight relative to a 2015 or newer light-duty vehicle. The fuel economy goal was achieved by designing an engine incorporating high geometric compression ratio, high dilution tolerance, low pumping work, and low friction. The increased tendency for knock with high compression ratio was addressed using early intake valve closing (EIVC), cooled exhaust gas recirculation (EGR), an active pre-chamber ignition system, and careful management of the fresh charge temperature.

In recent years, the automotive industry has seen an exponential increase in the replacement of mechanical components with electronic-controlled components or systems. engine, transmission, brake, exhaust gas recirculation (EGR), lighting, driver-assist technologies, etc. are all monitored and/or controlled electronically. Connected vehicles are increasingly being used by Original Equipment Manufacturers (OEMs) to collect and transmit vehicle data in real-time via the use of various sensors, actuators, and communication technologies. Vehicle telematics devices can collect and transmit data about the vehicle location, speed, fuel efficiency, State Of Charge (SOC), auxiliary battery voltage, emissions, performance, and more. This data is sent over to the cloud via cellular networks, where it can be processed and analyzed to improve their products and services by automotive companies and/or fleet management.

With the proliferation of ADAS and autonomous systems, the quality and quantity of the data to be used by vehicles has become crucial. In-vehicle sensors are evolving, but their usability is limited to their field of view and detection distance. V2X communication systems solve these issues by creating a cooperative perception domain amongst road users and the infrastructure by communicating accurate, real-time information. In this paper, we propose a novel Consolidated Object Data Service (CODS) for multi-Radio Access Technology (RAT) V2X communication. This service collects information using BSM packets from the vehicular network and perception information from infrastructure-based sensors. The service then fuses the collected data, offering the communication participants with a consolidated, deduplicated, and accurate object database. Since fusing the objects is resource intensive, this service can save in-vehicle computation costs.

The previously developed power-based fuel consumption theory for Internal Combustion Engine Vehicles (ICEV) is extended to Battery Electric Vehicles (BEV). The main difference between the BEV model structure and the ICEV is the bi-directional character of traction motors and batteries. A traction motor model was developed as a bi-linear function of positive and negative traction power. Another difference is that the accessories and cabin heating are powered directly from the battery, and not from the powertrain. The resulting unified model for ICEV and BEV energy consumption has linear terms proportional to positive and negative traction power, accessory power, and overhead, in varying proportions. Compared to the ICEV, the BEV powertrain has a high marginal efficiency and low overhead. As a result, BEV energy consumption data under a wide range of driving conditions are mainly proportional to net traction power, with only a small offset.

By utilizing the vehicle to infrastructure communication, the conventional Green Light Optimized Speed Advisory (GLOSA) applications give speed advisory range for drivers to travel to pass at the green light. However, these systems do not consider the traffic between the ego vehicle and the traffic light location, resulting in inaccurate speed advisories. Therefore, the driver needs to intuitively adjust the vehicle's speed to pass at the green light and avoid traffic in these scenarios. Furthermore, inaccurate speed advisories may result in unnecessary acceleration and deceleration, resulting in poor fuel efficiency and comfort. To address these shortcomings of conventional GLOSA, in this study, we proposed the utilization of collaborative perception messages shared by smart infrastructures to create an enhanced speed advisory for the connected vehicle drivers and automated vehicles.

In this paper, we present an end-to-end real-time detection and collision avoidance framework in an autonomous vehicle using a monocular RGB camera. The proposed system is able to run on embedded hardware in the vehicle to perform real-time detection of small objects. RetinaNet architecture with ResNet50 backbone is used to develop the object detection model using RGB images. A quantized version of the object detection inference model is implemented in the vehicle using NVIDIA Jetson AGX Xavier. A geometric method is used to estimate the distance to the detected object which is forwarded to a MicroAutoBox device that implements the control system of the vehicle and is responsible for maneuvering around the detected objects. The pipeline is implemented on a passenger vehicle and demonstrated in challenging conditions using different obstacles on a predefined set of waypoints.

Studies regarding the automotive communication networks has been a fast-growing subject of research through automotive companies. One of the main issues during a vehicle network prototype development is the necessity of a programmed hardware for gateway modules. The gateway developed by an automotive supplier, usually implemented at an Electronic Control Unit (ECU), is one of the last remaining modules to have a software available because it needs to wait the message list completion of all ECUs prior to set up its own message list and network interfaces. This paper proposes a method to design and test Controlled Area Network (CAN) gateways using Vector CANoe software by developing ways to facilitate a scalable code production in CAPL scripts. Use cases will use gatewayed signals virtually validated prior to software deployment, along with codes proposals and common cases examples.

A novel surrogate model is presented, which predicts the engine-out Particle Number (PN) emissions of a light-duty, spray-guided, turbo-charged, GDI engine. The model is developed through extensive CFD analysis, carried out using the Siemens Simcenter STAR-CD, and considers a range of part-load operating conditions and single-variable sweeps where control parameters such as start of injection and injection pressure are varied in isolation. The work is attached to the Ford-led APC6 DYNAMO project, which aims to improve efficiency and reduce harmful emissions from the next generation of gasoline engines. The CFD work focused on the air exchange, fuel spray and mixture preparation stages of the engine cycle. A combined Rosin-Rammler and Reitz-Diwakar model, calibrated over a wide range of injection pressure, is used to model fuel atomization and secondary droplets break-up.

The ported shroud casing treatment for turbocharger compressors offers a wider operating flow range, elevated boost pressures at low compressor mass flow rates, and reduced broadband whoosh noise in spark-ignition internal combustion engine applications. However, the casing treatment elevates tonal noise at the blade-pass frequency (BPF). Typical rotational speeds of compressors employed in practice push BPF noise to high frequencies, which then promote multi-dimensional acoustic wave propagation within the compressor ducting. As a result, in-duct acoustic measurements become sensitive to the angular location of pressure transducers on the duct wall. The present work utilizes a steady-flow turbocharger gas stand featuring a unique rotating compressor inlet duct to quantify the variation of noise measured around the duct at different angular positions.

A cast magnesium AE44 subframe was designed and manufactured for a C Class sedan to reduce weight and improve vehicle fuel economy. Corrosion mitigation strategies were developed to reduce the likelihood of galvanic corrosion. Both a proving ground vehicle corrosion test and a laboratory component corrosion test were conducted. The vehicle test result demonstrated that the corrosion mitigation strategies were effective. They also provided lessons learned on clearance between magnesium and steel components and options to improve the subframe’s corrosion resistance. The magnesium subframe achieved 5 kg (32%) weight reduction from the equivalent steel subframe and met all the required structural performance targets.

A cast magnesium subframe was designed and manufactured for a C Class sedan to reduce weight and improve vehicle fuel economy. The magnesium subframe achieved 5 kg (32%) weight reduction from the equivalent steel subframe and met all the required structural performance targets. All the joints of the magnesium subframe were tested for bolt load retention. The tests were conducted with a temperature profile of 100°C to -30°C designed to investigate the creep behavior of the selected magnesium alloy AE44 under high stress.

The software gradually takes over more and more tasks of the driver and paves the way to autonomous driving. Software development and software verification is therefore crucial for manufacturer's success. Standards such as ISO 26262 highly recommend requirements-based verification. Agile development uses continuous integration testing based on test automation and evaluation. All this pushed the creation of a model-based software verification environment that provides test generation and test automatization for all kinds of signal-based tests along the V-model. This paper presents a novel core component of this environment, which is as far as to the extent possible a standard-compliant cloud-based solution to test automation at the hardware level. Based on characteristic properties of testbenches, such as the wiring or the connected ECUs, hardware resources available at remote locations can be fully automated.

Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system’s structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems.

Fuel power consumption for light duty vehicles has previously been shown to be proportional to vehicle traction power, with an offset for overhead and accessory losses. This allows the fuel consumption for an individual powertrain to be projected across different vehicles, missions, and drive cycles. This work applies the power-based model to commercial vehicles and demonstrates its usefulness for projecting fuel consumption on both regulatory and customer use cycles. The ability to project fuel consumption to different missions is particularly useful for commercial vehicles, as they are used in a wide range of applications and with customized designs. Specific cases are investigated for Light and Medium Heavy- Duty work trucks. The average power required by a vehicle to drive the regulatory cycles varies by nearly a factor 10 between the Class 4 vehicle on the ARB Transient cycle and the loaded Class 7 vehicle at 65 mph on grade.

A torque converter is a type of fluid coupling device used to transfer engine power to the gearbox and driveline. A bypass clutch equipped in a torque converter assembly is a friction element which when fully engaged, can directly connect the engine to the gearbox. The torque converter is an important launch device in an automatic transmission which decouples engine speed from gearbox input speed while providing torque multiplication to drive the vehicle. During partial pedal launch, it is desired to engage the bypass clutch early and reduce the converter slippage in order to reduce power loss and achieve better fuel economy. However, engaging the bypass clutch early and aggressively may disturb the wheel torque and cause unpleasant driving experiences. This paper describes a multi-input multi-output (MIMO) control method to coordinate both engine and converter bypass clutch to simultaneously deliver desired wheel torque and reduce converter slippage.

There are a variety of test protocols associated with vehicle fuel economy and emissions testing. As a result, a number of test protocols currently exist to measure axle efficiency and spin loss. The intent of this technical paper is to describe a methodology that uses a singular axle efficiency and spin loss procedure. The data can then be used to predict the effects on vehicle FE and GHG for a specific class of vehicles via simulation. An accelerated break-in method using a comparable energy approach has been developed, and can be used to meet the break-in requirements of different vehicle emission test protocols. A “float to equilibrium” sump temperature approach has been used to produce instantaneous efficiency data, which can be used to more accurately predict vehicle FE and GHG, inclusive of Cold CO2. The “Float to Equilibrium” approach and “Fixed Sump Temperature” approach has been compared and discussed.

This paper describes development of an integrated regenerative braking system and anti-lock brake system (ABS) control during an ABS event for hybrid and electric vehicles with drivelines containing a single electric motor connected to the axle shaft through an open differential. The control objectives are to recuperate the maximum amount of kinetic energy during an ABS event, and to provide no degraded anti-lock control behavior as seen in vehicles with regenerative braking disabled. The paper first presents a detailed control system analysis to reveal the inherent property of non-zero regenerative braking torque control during ABS event and explain the reason why regenerative braking torque can increase the wheel slip during ABS event with existing regenerative braking control strategies.

Optimization of heavy materials like steel, in order to create a lighter vehicle, it is a major goal among most automakers, since heavy vehicles simply cannot compete with a lightweight model's fuel economy. Thinking this way, this paper shows a case study where the Size Optimization technique is applied to a front floor reinforcement. The reinforcement is used by two different vehicles, a subcompact and a crossover Sport Utility Vehicle (SUV), increasing the problem complexity. The Size Optimization technique is supported by Finite Element Method (FEM) tools. FEM in Computer Aided Engineering (CAE) is a numerical method for solving engineering problems, and its use can help to optimize prototype utilization and physical testing.