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Fault diagnosis for automotive systems is driven by government regulations, vehicle repairability, and customer satisfaction. Several methods have been developed to detect and isolate faults in automotive systems, subsystems and components with special emphasis on those faults that affect the exhaust gas emission levels. Limit checks, model-based, and knowledge-based methods are applied for diagnosing malfunctions in emission control systems. Incipient and partial faults may be hard to detect when using a detection scheme that implements any of the previously mentioned methods individually; the integration of model-based and knowledge-based diagnostic methods may provide a more robust approach. In the present paper, use is made of fuzzy residual evaluation and of a fuzzy expert system to improve the performance of a fault detection method based on a mathematical model of the engine.

Recent studies in sheet metal forming, conducted at universities world wide, emphasize the development of computer aided techniques for process simulation. To be practical and acceptable in a production environment, these codes must be easy to use and allow relatively quick solutions. Often, it is not necessary to make exact predictions but rather to establish the influence of process variables upon part quality, tool stresses, material flow, and material thickness variation. In cooperation with its industrial partners, the ERC for Net Shape Manufacturing of the Ohio State University has applied a number of computer codes for analysis and design of sheet metal forming operations. This paper gives a few selected examples taken from automotive applications and illustrates practical uses of computer simulations to improve productivity and reduce tool development and manufacturing costs.

Automating road vehicle control can increase the range and reliability of dynamic testing. Some tests, for instance, specify precise steering inputs which human test drivers are only able to approximate, adding uncertainty to the test results. An automated steering system has been developed which is capable of removing these limitations. This system enables any production car or light truck to follow a user-defined path, using global position feedback, or to perform specific steering sequences with excellent repeatability. The system adapts itself to a given vehicle s handling characteristics, and it can be installed and uninstalled quickly without damage or permanent modification to the vehicle.

Delivery trucks and vans represent a growing transportation segment which reflects the shift of consumers towards on-line shopping and on-demand delivery. Therefore, electrification of this class of vehicles is going to play a major role in the decarbonization of the transportation sector and in the transition to a sustainable mobility system. Hybrid electric vehicles can represent a medium-term solution and have gained an increasing share of the market in recent years. These vehicles include two power sources, typically an internal combustion engine and a battery, which gives more degrees of freedom when controlling the powertrain to satisfy the power request at the wheels. Components sizing and powertrain energy management are strongly coupled and can make a substantial impact on the final energy consumption of a hybrid vehicle.

Electrochemical models of lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided engineering design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models.

Plug-In Hybrid Vehicles (PHEVs) represent the middle point between Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs), thus combining benefits of the two architectures. PHEVs can achieve very high fuel economy while preserving full functionality of hybrids - long driving range, easy refueling, lower emissions etc. These advantages come at an expense of added complexity in terms of available fuel. The PHEV battery is recharged both though regenerative braking and directly by the grid thus adding extra dimension to the control problem. Along with the minimization of the fuel consumption, the amount of electricity taken from the power grid should be also considered, therefore the electricity generation mix and price become additional parameters that should be included in the cost function.

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output.

A prototype hybrid exhaust silencing system consisting of dissipative and reactive components is designed based on the boundary element method (BEM) with a specific emphasis on its acoustic performance as evaluated relative to a production system. The outer dimensions of the prototype system are comparable to its production counterpart, which has two silencers connected by a pipe. The predicted transmission loss by BEM for the prototype is compared with the experimental results in an impedance tube for both the prototype and production hardware, providing a design guidance for the former. The sound pressure levels measured at the tailpipe exit during the engine ramp-up experiments in a dynamometer laboratory are presented to compare the two systems, providing the final assessment.

Springback affects the dimensional accuracy and final shape of stamped parts. Accurate prediction of springback is necessary to design dies that produce the desired part geometry and tolerances. Springback occurs after stamping and ejection of the part because the state of the stresses and strains in the deformed material has changed. To accurately predict springback through finite element analysis, the material model should be well defined for accurate simulation and prediction of stresses and strains after unloading. Despite the development of several advanced material models that comprehensively describe the Bauschinger effect, transient behavior, permanent softening of the blank material, and unloading elastic modulus degradation, the prediction of springback is still not satisfactory for production parts. Dies are often recut several times, after the first tryouts, to compensate for springback and achieve the required part geometry.

Many automotive components and sub-systems require viscoelastic damping treatments to control noise and vibration characteristics. To aid the dynamic design process, new approaches are needed for modeling of partial damping treatments and characterization of the overall dynamic behavior. The analytical component of the design process is illustrated via the transmission casing cover, along with supporting experiments. First, the vibration response of production casing plates is examined, with and without the constrained layer treatment. A modified flat plate is employed along with a generic housing that provides the realistic boundary conditions for subsequent work. A simplified analytical damping model for constrained viscoelastic layer damping is suggested based on assumed modal functions. Using the analytical model, design guidelines in terms of optimal patch shapes and locations are suggested.

The study emphasizes transitioning school buses from diesel to electric to mitigate their environmental impact, addressing challenges like limited driving range through predictive models. This research introduces a comprehensive control-oriented model for estimating auxiliary loads in electric school buses. It begins by developing a transient thermal model capturing cabin behavior, divided into passenger and driver zones. Integrated with a control-oriented HVAC model, it estimates heating and cooling loads for desired cabin temperatures under various conditions. Real-world operational data from school bus specifications enhance the model’s practicality. The models are calibrated using experimental cabin-HVAC data, resulting in a remarkable overall Root Mean Square Error (RMSE) of 2.35°C and 1.88°C between experimental and simulated cabin temperatures.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 51 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the fabrication and control implementation process followed by the Ohio State team during Year 2 of the competition. The fabrication process includes finalizing designs based on identified requirements, building and assembling components, and performing extensive validation testing on the mechanical, electrical and control systems.

A dynamometer test methodology was developed for evaluation of HMMWV axle efficiency with hypoid gearsets, comparing those having various degrees of superfinish versus new production axles as well as used axles removed at depot maintenance. To ensure real-world applicability, a HMMWV variant vehicle model was created and simulated over a peacetime vehicle duty cycle, which was developed to represent a mission scenario. In addition, tractive effort calculations were then used to determine the maximum input torques. The drive cycle developed above was modified into two different profiles having varying degrees of torque variability to determine if the degree of variability would have a significant influence on efficiency in the transient dynamometer tests. Additionally, steady state efficiency performance is measured at four input pinion speeds from 700-2500 rpm, five input torques from 50 - 400 N⋅m, and two sump temperatures, 80°C and 110°C.

In order to improve the vehicle’s fuel economy while in cruise, the Model Predictive Control (MPC) technology has been adopted utilizing the road grade preview information and allowance of the vehicle speed variation. In this paper, a focus is on robustness study of delivered fuel economy benefit of Adaptive Nonlinear Model Predictive Controller (ANLMPC) reported earlier in the literature to several noise factors, e.g. vehicle weight, fuel type etc. Further, the vehicle position is obtained via GPS with finite precision and source of road grade preview might be inaccurate. The effect of inaccurate information of the road grade preview on the fuel economy benefits is studied and a remedy to it is established.

Driver’s license examinations require the driver to perform either a parallel parking or a similar maneuver as part of the on-road evaluation of the driver’s skills. Self-driving vehicles that are allowed to operate on public roads without a driver should also be able to perform such tasks successfully. With this motivation, the S-shaped maneuverability test of the Ohio driver’s license examination is chosen here for automatic execution by a self-driving vehicle with drive-by-wire capability and longitudinal and lateral controls. The Ohio maneuverability test requires the driver to start within an area enclosed by four pylons and the driver is asked to go to the left of the fifth pylon directly in front of the vehicle in a smooth and continuous manner while ending in a parallel direction to the initial one. The driver is then asked to go backwards to the starting location of the vehicle without stopping the vehicle or hitting the pylons.

The practical and proven use of computers in forming technology include: CAD/CAM for die making; transfer of geometric data from the customer's CAD/CAM system to that of the supplier and vice versa; application of artificial intelligence and expert systems for part and process design; simulation of metal flow to eliminate forging defects; prediction and optimization of process variables; and analysis of stresses in dies as well as prevention of premature die failure. Intelligent use of this information can lead to significant gains in product quality and productivity. This paper presents three examples of application of process simulation to forming : rolling, ring rolling and forging.

The EcoCAR 2 team at the Ohio State University has designed an extended-range electric vehicle capable of 44 miles all-electric range, which features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and a 6-speed automated manual transmission. This vehicle is designed to reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report documents the team's refinement work on the vehicle during Year 3 of the competition, including vehicle improvements, control strategy calibration and dynamic vehicle testing, culminating in a 99% buy off vehicle that meets the goals set forth by the team. This effort was made possible through support from the U.S. Department of Energy, General Motors, The Ohio State University, and numerous competition and local sponsors.

The coupling of shear layer instabilities with the acoustic resonances at the interface of two ducts, a main duct and a connecting sidebranch, leads to whistle noise. The present study investigates experimentally the mechanism of such pure tone noise. A generic sidebranch adapter is fabricated to allow for: (1) the ability to mount downstream of the throttle body in the induction system of a production engine; (2) the adjustment of sidebranch length; and (3) the changes in the diameter of the branch duct. Experiments are conducted both in a flow facility and an engine dynamometer facility for the same set of flow rates. The correlation of the whistle noise between these two facilities is examined in terms of frequency and the dimensionless numbers, including Strouhal and Mach.

The Ohio State University EcoCAR 3 team is building a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of improving fuel economy and reducing tail pipe emissions, the Ohio State Camaro has been fitted with a 32 kW alternator-starter belt coupled to a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85). The belted alternator starter (BAS) which aids engine start-stop operation, series mode and torque assist, is powered by an 18.9 kWh Lithium Iron Phosphate energy storage system, and controlled by a DC-AC inverter/controller. This report details the modeling, calibration, testing and validation work done by the Ohio State team to fast track development of the BAS system in Year 2 of the competition.

With the availability of advanced machine designs and controls, tube hydroforming has become an economic alternative to various stamping processes. The technology is relatively new so that there is no large “knowledge base” to assist the product and process designers. This paper reviews the fundamentals of tube hydroforming technology and discusses how various parameters, such as tube material properties, pre-form geometry, lubrication and process control affect product design and quality. In addition, relations between process variables and achievable part geometry are discussed. Finally, using examples, the status of the current technology and critical issues for future development are reviewed.