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Two-stage turbochargers are a recent solution to improve engine performance. The large flexibility of these systems, able to operate in different modes, can determine a reduction of the turbo-lag phenomenon and improve the engine tuning. However, the presence of two turbochargers that can be in part operated independently requires effort in terms of analysis and optimization to maximize the benefits of this technology. In addition, the design and calibration of the control system is particularly complex. The transitioning between single stage and two-stage operations poses further control issues. In this scenario a model-based approach could be a convenient and effective solution to investigate optimization, calibration and control issues, provided the developed models retain high accuracy, limited calibration effort and the ability to run in real time.

This paper describes the development and experimental validation of a Plug-in Hybrid Electric Vehicle (PHEV) dynamic simulator that enables development, testing, and calibration of a traction control strategy. EcoCAR 2 is a three-year competition between fifteen North American universities, sponsored by the Department of Energy and General Motors that challenges students to redesign a Chevrolet Malibu to have increased fuel economy and decreased emissions while maintaining safety, performance, and consumer acceptability. The dynamic model is developed specifically for the Ohio State University EcoCAR 2 Team vehicle with a series-parallel PHEV architecture. This architecture features, in the front of the vehicle, an ICE separated from an automated manual transmission with a clutch as well as an electric machine coupled via a belt directly to the input of the transmission. The rear powertrain features another electric machine coupled to a fixed ratio gearbox connected to the wheels.

The definition of the energy management strategy for a hybrid electric vehicle is a key element to ensure maximum energy efficiency. The ability to optimally manage the on-board energy sources, i.e., fuel and electricity, greatly affects the final energy consumption of hybrid powertrains. In the case of plug-in series-hybrid architectures, such as Range-Extender Electric Vehicles (REEVs), fuel efficiency optimization alone can result in a stressful operation of the range-extender engine with an excessively high number of start/stops. Nonetheless, reducing the number of start/stops can lead to long periods in which the engine is off, resulting in the after-treatment system temperature to drop and higher emissions to be produced at the next engine start.

When developing a new engine control strategy, some of the important issues are cost, resource minimization, and quality improvement. This paper outlines how a model based approach was used to develop an engine control strategy for an Extended Range Electric Vehicle (EREV). The outlined approach allowed the development team to minimize the required number of experiments and to complete much of the control development and calibration before implementing the control strategy in the vehicle. It will be shown how models of different fidelity, from map-based models, to mean value models, to 1-D gas dynamics models were generated and used to develop the engine control system. The application of real time capable models for Hardware-in-the-Loop testing will also be shown.

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 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 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the rigorous design process followed by the Ohio State team during Year 1 of the competition. The design process includes identifying the team customer's needs and wants, selecting an overall vehicle architecture and completing detailed design work on the mechanical, electrical and control systems. This effort was made possible through support from the U.S.

Homogeneous Charge Compression Ignition (HCCI) is considered a very promising concept to achieve low NOx and Particulate Matter emissions in traditional spark ignition and Diesel engines. However, controlling the complex mechanisms which govern the combustion process and finding a proper method for the fuel introduction for Diesel HCCI engines have proven to still be a challenge. In addition, the well known IMEP limitations of HCCI combustion restrict the benefits on emissions to low engine load conditions. The current work attempts to extend the benefits of HCCI combustion to a broader range of engine operating conditions by blending the conventional Direct Injection (DI) with the external fuel atomization. A dual combustion system could potentially overcome the limits of low-load operations and allow for a gradual transition between the conventional DI mode at high load and the HCCI external mixture formation at idle and low load.

Electronic throttle control is increasingly being considered as a viable alternative to conventional air management systems in modern spark-ignition engines. In such a scheme, driver throttle commands are interpreted by the powertrain control module together with many other inputs; rather than directly commanding throttle position, the driver is now simply requesting torque - a request that needs to be appropriately interpreted by the control module. Engine management under these conditions will require optimal control of the engine torque required by the various vehicle subsystems, ranging from HVAC, to electrical and hydraulic accessories, to the vehicle itself. In this context, the real-time estimation of engine and load torque can play a very important role, especially if this estimation can be performed using the same signals already available to the powertrain control module.

The integrity of the exhaust emission system in a passenger vehicle can best be maintained by monitoring its performance continuously on board the vehicle. It is with the intent of monitoring emission system performance that the California Air Resources Board has proposed regulations which will require vehicles to be equipped with on-board monitoring systems. These proposed regulations are known as OBDII and will probably be followed by similar Federal EPA regulations.This paper discusses a method of monitoring engine misfire as part of the OBDII requirements for passenger vehicle on-board diagnostics. The method is relatively inexpensive in that it uses an existing sensor for measuring instantaneous crankshaft angular position, and utilizes electronic signal processing which can be implemented in relatively inexpensive custom integrated circuits.

An appropriate fault diagnosis and Isolation (FDI) strategy is very useful to prevent system failure. In this paper, a model-based fault diagnosis strategy is developed for an internal combustion engine (ICE) under speed control. Engine throttle fault and the manifold pressure sensor fault are detected and isolated. A nonlinear observer based residual generation approach is proposed. Manifold pressure and throttle are observed. Fault codes are designed with redundancy to prevent bit error. Performance of fault diagnosis strategy has been evaluated with simulations.

This paper presents the implementation and performance of an electric all-wheel drive system on a series-parallel, through-the-road hybrid electric vehicle. Conventional methods of all-wheel drive do not provide a suitable solution for this type of vehicle as the powertrain lacks a mechanical link between the front and rear axles. Moreover, this unique architecture allows the vehicle to be propelled solely by the front, or the rear, wheels during typical operation. Thus, the algorithm presented here manages wheel slip by either the front, or rear wheels when engaging to provide all-wheel drive capability. necessary testing validates the robustness of this Extensive system.

Traditionally in the United States, Diesel engines have negative connotations, primarily due to their association with heavy duty trucks, which are wrongly characterized as “dirty.” Diesel engines are more energy efficient and produce less carbon dioxide than gasoline engines, but their particulate and NOx emissions are more difficult to reduce than spark ignition engines. To tackle this problem, a number of after-treatment technologies are available, such as Diesel Lean NOx Traps (LNTs)), which reduces oxides of nitrogen, and the Diesel particulate filter (DPF), which reduces particulate matter. Sophisticated control techniques are at the heart of these technologies, thus making Diesel engines run cleaner. Another potentially unattractive aspect of Diesel engines is noise.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Two-stage turbochargers are a recent solution to improve engine performance, reducing the turbo-lag phenomenon and improving the matching. However, the definition of the control system is particularly complex, as the presence of two turbochargers that can be in part operated independently requires effort in terms of analysis and optimization. This work documents a characterization study of two-stage turbocharger systems. The study relies on a mean-value model of a Diesel engine equipped with a two-stage turbocharger, validated on experimental data. The turbocharger is characterized by a VGT actuator and a bypass valve (BPV), both located on the high-pressure turbine. This model structure is representative of a “virtual engine”, which can be effectively utilized for applications related to analysis and control. Using this tool, a complete characterization was conducted considering key operating conditions representative of FTP driving cycle operations.

New vehicle technologies open up a vast number of new options for the designer, removing traditional constraints. Some recent conceptual designs, such as GM's Hy-wire, have recognized this and offered innovative new architectures. Unfortunately, many other new technology concept cars do not exploit the freedoms of the new technologies, hampering themselves with traditional design cues developed for conventional powertrains. This paper will present the conceptual design of a high-power, high-speed fuel cell luxury sedan. One of the main motivations of this case study was to explore what could happen when a vehicle was designed from the ground up as a fuel cell vehicle, optimized at the overall system level as well as at the individual component level. The paper will discuss innovations in vehicle architecture and novel concepts for the electrical transmission, fuel cell system and electromagnetic suspension.

In recent years, the increasing interest and requirements for improved engine diagnostics and control has led to the implementation of several different sensing and signal processing technologies. In order to optimize the performance and emission of an engine, detailed and specified knowledge of the combustion process inside the engine cylinder is required. In that sense, the torque generated by each combustion event in an IC engine is one of the most important variables related to the combustion process and engine performance. This paper introduces torque estimation techniques in the real-time basis for engine control applications using the measurement of crankshaft speed variation. The torque estimation scheme presented in this paper consists of two entirely different approaches, “Stochastic Analysis” and “Frequency Analysis”.

This paper shall present the design and development of a family of high power, high-speed transport and combat vehicles based on a common module. The system looks to maximize performance at both high-speed operation and low-speed, heavy/severe-duty operation. All-wheel drive/steer-by-wire autonomous traction modules provide the basis for the vehicle family. Each module can continuously develop 300-400 kW of power at the wheels and has nearly double peak capability, exploiting the flexibility of the electric traction system. The maximum starting tractive effort developed by one module can reach 10-15 tons, and the full rated power can be produced at speeds of 100 mph. This paper will present the design and layout of the autonomous modules. Details will be provided about the tandem electric axles, with electric differentials and independent steering.

The paper presents a possible concept design for integration of individual wheel AC motors into Oshkosh Truck Corporation's InDependent Suspension. A new axle concept design (including drive line and CV-joint) is presented with a new AC induction motor concept. Both concepts are able to match 100% the sever-heavy duty requirements in a large area of advanced on and off road traction applications. Concepts are suitable for modularity in a multi-axle (2-6) All-Wheel Drive, All Steer configuration vehicle.

This paper presents the conceptual design of a high-power, high-speed tractor-trailer for severe duty applications. Design of the tractor-trailer introduces several new concepts, including the general vehicle architecture, a new electrical transmission system and a new electric tandem axle. The vehicle architecture consists of a low drag cab concept with a fully integrated turbo-generator power source, an exhaust gas electric decontamination system and auxiliaries. The electric transmission introduces a new combination of electrical machines and power electronics designed to perform under maximum load with minimum dimension, weight and price. The electric tandem axle is a new concept of an all-wheel steering independent suspension with virtual electromagnetic differential.

The stochastic Fault Detection and Isolation (FDI) algorithm, known as the statistical local approach, is applied in a model-based framework to the diagnosis of component faults in the air-intake system of an automotive engine. The FDI scheme is first presented as a general methodology that permits the detection of faults in complex nonlinear systems without the need for building inverse models or numerous observers. Although sensor and actuator faults can be detected by this FDI methodology, component faults are generally more difficult to diagnose. Hence, this paper focuses on the detection and isolation of component faults for which the local approach is especially suitable. The challenge is to provide robust on-board diagnostics regardless of the inherent nonlinearities in a system and the random noise present.

This paper introduces a new series of empirical mathematical models developed to characterize brake torque generation of pneumatically actuated Class-8 vehicle brakes. The brake torque models, presented as functions of brake chamber pressure and application speed, accurately simulate steer axle, drive axle, and trailer tandem brakes, as well as air disc brakes (ADB). The contemporary data that support this research were collected using an industry standard inertia-type brake dynamometer, routinely used for verification of FMVSS 121 commercial vehicle brake standards.