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In June of 2015, the Environmental Protection Agency and the National Highway Traffic Safety Administration issued a Notice of Proposed Rulemaking to further reduce greenhouse gas emissions and improve the fuel efficiency of medium- and heavy-duty vehicles. The agencies proposed that vehicle manufacturers would certify vehicles to the standards by using the agencies’ Greenhouse Gas Emission Model (GEM). The agencies also proposed a steady-state engine test procedure for generating GEM inputs to represent the vehicle’s engine performance. In the proposal the agencies also requested comment on an alternative engine test procedure, the details of which were published in two separate 2015 SAE Technical Papers [1, 2]. As an alternative to the proposed steady-state engine test procedure, these papers presented a cycle-average test procedure.

In 2015 the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation's National Highway Traffic Safety Administration (NHTSA) proposed a new steady-state engine dynamometer test procedure by which heavy-duty engine manufacturers would be required to create engine fuel rate versus engine speed and torque “maps”.[1] These maps would then be used within the agencies' Greenhouse Gas Emission Model (GEM)[2] for full vehicle certification to the agencies' proposed heavy-duty fuel efficiency and greenhouse gas (GHG) emissions standards. This paper presents an alternative to the agencies' proposal, where an engine is tested over the same duty cycles simulated in GEM. This paper explains how a range of vehicle configurations could be specified for GEM to generate engine duty cycles that would then be used for engine testing.

In designing a regulatory vehicle simulation program for determining greenhouse gas (GHG) emissions and fuel consumption, it is necessary to estimate the performance of technologies, verify compliance with the regulatory standards, and estimate the overall benefits of the program. The agencies (EPA/NHTSA) developed the Greenhouse Gas Emissions Model (GEM) to serve these purposes. GEM is currently being used to certify the fuel consumption and CO2 emissions of the Phase 1 rulemaking for all heavy-duty vehicles in the United States except pickups and vans, which require a chassis dynamometer test for certification. While the version of the GEM used in Phase 1 contains most of the technical and mathematical features needed to run a vehicle simulation, the model lacks sophistication. For example, Phase 1 GEM only models manual transmissions and it does not include engine torque interruption during gear shifting.

This paper presents the latest results for a new high efficiency clean diesel combustion system – Adaptive PCCI Combustion (a premixed charge compression ignition mixed-mode combustion) using a micro-variable circular orifice (MVCO) fuel injector. Key characteristics of the new combustion system such as low NOx and soot emissions, high fuel efficiency, increased engine torque are presented through KIVA simulation results. While early premixed charge compression ignition (PCCI) combustion reduces engine-out NOx and soot, it's limited to partial loads by known issues such as combustion control, high HC and CO, and high pressure rise rate, etc. Conventional combustion is well controlled diffusion combustion but comes with high NOx and soot. Leveraging the key merits of PCCI and conventional combustion in a practical engine is both meaningful and challenging.

A multi-objective genetic algorithm methodology was applied to a heavy-duty diesel engine at three different operating conditions of interest. Separate optimizations were performed over various fuel injection nozzle parameters, piston bowl geometries and swirl ratios (SR). Different beginning of injection (BOI) timings were considered in all optimizations. The objective of the optimizations was to find the best possible fuel economy, NOx, and soot emissions tradeoffs. The input parameter ranges were determined using design of experiment methodology. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. For the optimization of piston bowl geometry, an automated grid generator was used for efficient mesh generation with variable geometry parameters. The KIVA3V release 2 code with improved ERC sub-models was used. The characteristic time combustion (CTC) model was employed to improve computational efficiency.

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.

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.

Heavy-duty natural gas engines available today are typically derived from diesel engines. The biggest discrepancy in thermal efficiency between a natural gas engine and its diesel counterpart comes at low loads. This is particularly true for a lean-burn throttle-controlled refuse hauler. Field data shows that a refuse hauler operates at low speeds for the majority of the time, averaging between 3 to 7 miles per hour. As a result, many developers focus primarily on the improvement of thermal efficiency at light loads and low speeds. One way to improve efficiency at light loads is through the use of a late intake valve closing (IVC) technique. With the increase in electronic and hydraulic control technologies, the potential benefits of late IVC with unthrottled control are realizable in production engines.

An engine cycle simulation program has been developed to predict both engine performance and NOx emission with reasonable accuracy. The program is a product that combines two programs, VIPRE™ and ALAMO_ENGINE, both developed at Southwest Research Institute (SwRI). VIPRE™ is a comprehensive tool for engine systems with intake and exhaust dynamics, emphasizing engine performance [1], while ALAMO_ENGINE is a program focusing on NOx prediction [2]. Demonstrations in this paper were based on a six-cylinder, turbocharged diesel engine with a high-pressure exhaust gas recirculation (EGR) loop. The EGR system is connected upstream of the intake manifold from the exhaust manifold located in the turbine entrance. A two-way butterfly valve is used to control the EGR rate. The major challenge in this modeling work is the prediction of engine performance and NOx emission in an acceptable and systematical fashion.

Due to compressibility, reactivity, evaporation and mixing, the gas species concentration varies significantly along the intake and exhaust pipes of an engine. An understanding of this behavior is vital to correctly predict catalyst performance because the behavior of a catalyst very much depends on the instantaneous local species concentrations, rather than those in the cylinder. Also, knowing this behavior is more important to assess the effects of exhaust gas recirculation (EGR). The objective of this research is to develop a tool that is capable of predicting the instantaneous species concentration throughout the entire intake and exhaust system, and to lay out a foundation to model catalysts in the near future. This is done by first developing a complete engine cycle simulation model that is able to accurately predict wave dynamics in the piping system. Then, species tracking is accomplished by solving the species conservation equations.

Computer based analytical design techniques are transforming the engine design process. Analytical tools allow faster and more accurate design optimization. The design process is also shortened because the electronic transfer of files permits the design to be worked concurrently by engineers working with different analysis packages or on various parts of the design. Prototype parts and tooling can be made directly from the Computer-Aided Design (CAD) by various rapid prototyping methods. The analytical design techniques can also permit a highly optimized design with less possibility of corrections being necessary in the development stages. This paper reviews these new design techniques and examines how they can be used to improve the design technique. The following design tools are discussed.