Search Results

A neural network-based engine performance, fuel efficiency and emissions prediction system has been developed for both spark-ignited and compression ignition engines. Through limited training on an engine dynamometer, the neural network system is able to predict accurately real-time engine power output, fuel consumption and regulated exhaust emissions using readily measured engine parameters, across highly transient engine operating cycles. Applications for the models developed using this process include engine diagnostics, virtual sensing of unmeasured or unmeasurable engine emissions, engine control, and engine and vehicle modeling. Results from the prediction of the performance and emissions from a 300 hp CIDI engine and a 120 hp SI engine are presented, showing the potential of this newly developed approach.

Until a proper fueling infrastructure is established, vehicles powered by natural gas must have bi-fuel capability in order to avoid a limited vehicle range. Although bi-fuel conversions of existing gasoline engines have existed for a number of years, these engines do not fully exploit the combustion and knock properties of both fuels. Much of the power loss resulting from operation of an existing gasoline engine on compressed natural gas (CNG) can be recovered by increasing the compression ratio, thereby exploiting the high knock resistance of natural gas. However, gasoline operation at elevated compression ratios results in severe engine knock. The use of variable intake valve timing in conjunction with ignition timing modulation and electronically controlled exhaust gas recirculation (EGR) was investigated as a means of controlling knock when operating a bi-fuel engine on gasoline at elevated compression ratios.

Minimizing fuel consumption is emerging as the next major challenge for engine control and calibration, even as the requirements of complying with ever lower transient emissions regulations cannot be underestimated. Meeting these difficult and apparently conflicting emissions and efficiency goals is becoming increasingly onerous as engine and aftertreatment control complexity increases. Conventional engine calibration techniques are by nature time-intensive, ad-hoc and repetitive, resulting in low productivity of test facilities and engineering effort. Steady state engine mapping methods, such as design of experiments, do little to ensure transient emissions compliance or fuel consumption optimization. A new model-based Rapid Transient Calibration system has been developed, tested and validated using a 2007 production-specification Detroit Diesel Series 60 heavy-duty diesel engine.

Dedicated natural gas engines suffer the disadvantages of limited vehicle range and relatively few refueling stations. A vehicle capable of operating on either gasoline or natural gas allows alternative fuel usage without sacrificing vehicle range and mobility. However, the bi-fuel engine must be made to provide equal performance on both fuels. Although bi-fuel conversions have existed for a number of years, historically natural gas performance is degraded relative to gasoline due to reduced volumetric efficiency and lower power density of CNG. Much of the performance losses associated with CNG can be overcome by increasing the compression ratio. However, in a bi-fuel application, high compression ratios can result in severe engine knock during gasoline operation. Variable intake valve timing, increased exhaust gas recirculation and retarded ignition timing were explored as a means of controlling knock during gasoline operation of a bi-fuel engine.

Fuel efficiency optimization has emerged as the next major challenge in the field of diesel engine control and calibration. Conventional techniques will not be able to accommodate the many rigorous and competing demands placed on next generation engine control. An approach that holds great promise for future advanced transient engine control is model-based control (MBC). Model-based calibration optimization methods have shown their efficacy in the off-line engine development process, and these techniques can be extended to online, real-time engine control. This paper describes preliminary results from the deployment of MBC on a next generation heavy duty diesel engine. A description of the development process, the technologies that have been developed to exploit this process and the resultant proof-of-concept emissions and fuel consumption validation are provided.

As a part of the FutureTruck 2000 advanced technology student vehicle competition sponsored by the US Department of Energy and General Motors, West Virginia University has converted a full-size sport utility vehicle into a high fuel efficiency, low emissions vehicle. The environmental impact of the Chevrolet Suburban SUV, in terms of both greenhouse gas emissions and exhaust emissions, was reduced through hybridization without losing any of the functionality and utility of the base vehicle. The approach taken was one of using a high efficiency, state-of-the-art direct injection, turbocharged diesel engine coupled to a high output electric traction motor for power assist and to recover regenerative braking energy. The vehicle employs a state-of-the-art combination lean NOx catalyst, oxidation catalyst and particulate filter to ensure low exhaust emissions.

A project has been undertaken to optimize the engine control software calibration of a modern heavy-duty diesel engine for operation with gas-to-liquids (GTL) diesel fuel, with the objective of developing an understanding of the scope for optimization with this fuel, which has different physical and combustion properties to that of conventional, crude-derived diesel. A data-driven, model-based calibration technique utilizing artificial neural networks was used to develop optimized transient and steady-state calibrations with both conventional diesel fuel, as well as neat GTL fuel. The engine control parameters that were optimized were injection timing, exhaust gas recirculation rate, rail pressure, and charge mass. The optimization aimed to minimize fuel consumption without deterioration in engine-out nitrogen oxide (NOx) and soot emissions. This paper reports on the calibration optimization methodology employed and the results achieved to date.

With the adoption of complex technologies such as multiple injections, EGR and variable geometry turbocharging, it has become increasingly onerous to develop optimal engine control calibrations for either light- or heavy-duty diesel engines. The addition of NOx and PM aftertreatment systems increases further the calibration burden, as both diesel particulate filters and NOx absorbers require regeneration initiated by the engine management system. There is significant interest in the industry in reducing development costs by moving as much of the engine calibration process as is feasible from the engine test cell to the virtual desktop environment. This paper describes the development of a model-based calibration optimization system that offers significant advantages in reducing the time and effort required to obtain certification-quality engine calibrations.

Dual fuel engines employing pilot diesel injection to ignite premixed natural gas provide an opportunity for liquid petroleum fuel replacement and for reduced emissions of oxides of nitrogen (NOx) and particulate matter (PM). A Navistar T444E turbocharged V8 engine was converted to operate in dual fuel mode by metering the compressed natural gas (CNG) with an IMPCO Technologies, Inc. regulator and electronic valve while retaining the stock Navistar Hydraulically-Actuated Electronically-Controlled Unit Injection (HEUI) system for diesel pilot injection. A dedicated controller was designed and constructed to allow manual control of diesel fuel injection pulsewidth (FIPW), diesel injection advance (ADV), hydraulic injection control pressure (ICP) and natural gas mass flow. The controller employed two Microchip, Inc. PIC-based microcontrollers: one to perform initialization of a Silicon Systems, Inc. 67F867 engine interface peripheral, and the other to perform the runtime algorithms.

The emissions reduction benefits of Fischer-Tropsch (FT) diesel fuel have been shown in several recent published studies in both engine testing and in-use vehicle testing. FT diesel fuel shows significant advantages in reducing regulated engine emissions over conventional diesel fuel primarily to: its zero sulfur specification, implying reduced particulate matter (PM) emissions, its relatively lower aromaticity, and its relatively high cetane rating. However, the actual effect of FT diesel formulation on the in-cylinder combustion characteristics of unmodified modern heavy-duty diesel engines is not well documented. As a result, a Navistar T444E (V8, 7.3 liter) engine, instrumented for in-cylinder pressure measurement, was installed on an engine dynamometer and subjected to steady-state emissions measurement using both conventional Federal low sulfur pump diesel and a natural gas-derived FT fuel.

Pending GHG emissions reduction legislation for medium- and heavy-duty vehicles will require the development of engines and powertrains with significantly increased mechanical and electronic complexity. Increasing powertrain efficiency will require the simulation, control and calibration of an expanding number of highly interdependent air, fuel, exhaust, combustion and energy transfer subsystems. As a result of these increases in complexity, engine and powertrain control is becoming significantly more sophisticated and costly to develop and difficult to optimize. The high cost of developing engines and powertrain systems that demonstrate greater fuel efficiency and emissions benefits than the engines of today, is undeniable. The increased calibration burden and the complexity of optimization require the development and adoption of entirely new methods for transient engine calibration and optimization to achieve maximum vehicle fuel efficiency and lowest regulated emissions.