Search Results

Self-learning energy management is a promising concept, which optimizes real-world system performance by automated, on-line adaptation of control settings. In this work, the potential of self-learning capabilities related to optimization is studied for energy management in Plug-in Hybrid Electric Vehicles (PHEV). These vehicles are of great interest for the transport sector, since they combine high fuel efficiency with last mile full-electric driving. We focus on a specific use case: PHEV operation through future Zero Emission (ZE) zones of cities. As a first step towards self-learning control, we introduce a novel, adaptive supervisory controller that combines modular energy and emission management (MEEM) and deals with varying constraints and system uncertainty. This optimal control strategy is based on Pontryagin’s Minimum Principle and maximizes overall energy efficiency.

A model-based control approach is proposed to give proper reference for the feed-forward combustion control of Partially Pre-mixed Combustion (PPC) engines. The current study presents a simplified first principal model, which has been developed to provide a base estimation of the ignition properties. This model is used to describe the behavior of a single-cylinder heavy-duty diesel engine fueled with a mix of bio-butanol and n-heptane (80vol% bio-butanol and 20 vol% n-heptane). The model has been validated at 8 bar gross Indicated Mean Effective Pressure (gIMEP) in PPC mode. Inlet temperature and pressure have been varied to test the model capabilities. First the experiments were conducted to generate reference points with BH80 under PPC conditions. And then CFD simulations were conducted to give initial parameter set up, e.g. fuel distribution, zone dividing, for the multi-zone model.

CO2 regulations on heavy-duty transport are introduced in essentially all markets within the next decade, in most cases in several phases of increasing stringency. To cope with these mandates, developers of engines and related equipment are aiming to break new ground in the fields of combustion, fuel and hardware technologies. In this work, a novel diesel fuel injector, Delphi’s DFI7, is utilized to experimentally investigate and compare the performance of ramped injection rates versus traditional square fueling profiles. The aim is specifically to shift the efficiency and NOx tradeoff to a more favorable position. The design of experiments methodology is used in the tests, along with statistical techniques to analyze the data. Results show that ramped and square rates - after optimization of fueling parameters - produce comparable gross indicated efficiencies.

Reactivity Controlled Compression Ignition (RCCI) combines very high thermal efficiencies with ultra-low engine out NOx and PM emissions. Moreover, it enables the use of a wide range of fuels. As this pre-mixed combustion concept relies on controlled auto-ignition, closed-loop combustion control is essential to guarantee safe and stable operation under varying operating conditions. This work presents a coordinated air-fuel path controller for RCCI operation in a multi-cylinder heavy-duty engine. This is an essential step towards real-world application. Up to now, transient RCCI studies focused on individual cylinder control of the fuel path only. A systematic, model-based approach is followed to design a multivariable RCCI controller. Using the Frequency Response Function (FRF) method, linear models are identified for the air path and for the combustion process in the individual cylinders.

The operation of a dual fuel combustion engine using combustion mode-switching offers the benefit of higher thermal efficiency compared to single-mode operation. For various fuel combinations, the engine research community has shown that running dual fuel engines in Reactivity Controlled Compression Ignition (RCCI) mode, is a feasible way to further improve thermal efficiency compared to Conventional Dual Fuel (CDF) operation of the same engine. In RCCI combustion, also ultra-low engine-out NOx and soot emissions have been reported. Depending on available hardware, however, stable RCCI combustion is limited to a certain load range and operating conditions. Therefore, mode-switching is a promising way to implement RCCI in practice on short term. In this paper, a model-based development approach for a dual fuel mode-switching controller is presented. Simulation results demonstrate the potential of this controller for a heavy-duty engine running on natural gas and diesel.

Heavy-duty diesel engines are used in a wide range of applications. For varying operating environments, the engine and aftertreatment system must comply with the real-world emission legislation limits. Simultaneously, minimal fuel consumption and good drivability are crucial for economic competitiveness and usability. Meeting these requirements takes substantial development and calibration effort, and complying with regulations results in a trade-off between emissions and fuel consumption. TNO's Integrated Emission Management (IEM) strategy finds online, the cost-optimal point in this trade-off and is able to deal with variations in operating conditions, while complying with legislation limits. Based on the actual state of the engine and aftertreatment system, an optimal engine operating point is computed using a model-based optimal-control algorithm.

Heavy-duty diesel engines are used in different application areas, like long-haul, city distribution, dump truck and building and construction industry. For these wide variety of areas, the engine performance needs to comply with the real-world legislation limits and should simultaneously have a low fuel consumption and good drivability. Meeting these requirements takes substantial development and calibration effort, where an optimal fuel consumption for each application is not always met in practice. TNO's Integrated Emission Management (IEM) strategy, is able to deal with these variations in operating conditions, while meeting legislation limits and obtaining on-line cost optimization. Based on the actual state of the engine and aftertreatment, optimal air-path setpoints are computed, which balances EGR and SCR usage.

Cylinder pressure-based combustion control is widely introduced for passenger cars. Benefits include enhanced emission robustness to fuel quality variation, reduced fuel consumption due to more accurate (multi-pulse) fuel injection, and minimized after treatment size. In addition, it enables the introduction of advanced, high-efficient combustion concepts. The application in truck engines is foreseen, but challenges need to be overcome related to durability, increased system costs, and impact on the cylinder head. In this paper, a new single cylinder pressure sensor concept for heavy-duty Diesel engines is presented. Compared to previous studies, this work focuses on heavy-duty Diesel powertrains, which are characterized by a relatively flexible crank shaft in contrast to the existing passenger car applications.

For natural gas (NG)-diesel RCCI, a multi-zonal, detailed chemistry modeling approach is presented. This dual fuel combustion process requires further understanding of the ignition and combustion processes to maximize thermal efficiency and minimize (partially) unburned fuel emissions. The introduction of two fuels with different physical and chemical properties makes the combustion process complicated and challenging to model. In this study, a multi-zone approach is applied to NG-diesel RCCI combustion in a heavy-duty engine. Auto-ignition chemistry is believed to be the key process in RCCI. Starting from a multi-zone model that can describe auto-ignition dominated processes, such as HCCI and PCCI, this model is adapted by including reaction mechanisms for natural gas and NOx and by improving the in-cylinder pressure prediction. The model is validated using NG-diesel RCCI measurements that are performed on a 6 cylinder heavy-duty engine.

This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is considered to be standard for engine testing. The potential of the automated fit tool is demonstrated for two different heavy-duty diesel engines. This demonstrates that the combustion model and model fit methodology is not engine specific. Comparison of model and experimental results shows accurate prediction of in-cylinder peak pressure, IMEP, CA10, and CA50 over a wide operating range. This makes the model suitable for closed-loop combustion control development. However, NO emission prediction has to be improved.

Premixed combustion concepts like PCCI and RCCI have attracted much attention, since these concepts offer possibilities to reduce engine out emissions to a low level, while still achieving good efficiency. Most RCCI studies use a combination of a high-cetane fuel like diesel, and gasoline as low-cetane fuel. Limited results have been published using natural gas as low-cetane fuel; especially full scale engine results. This study presents results from an experimental study of diesel-CNG RCCI operation on a 6 cylinder, 8 l heavy duty engine with cooled EGR. This standard Tier4f diesel engine was equipped with a gas injection system, which used single point injection and mixed the gaseous fuel with air upstream of the intake manifold. For this engine configuration, RCCI operating limits have been explored. In the 1200-1800 rpm range, RCCI operation with Euro-VI engine out NOx and soot emissions was achieved between 2 and 9 bar BMEP without EGR.

This paper presents the identification and validation of a dynamic Waste Heat Recovery (WHR) system model. Driven by upcoming CO₂ emission targets and increasing fuel costs, engine exhaust gas heat utilization has recently attracted much attention to improve fuel efficiency, especially for heavy-duty automotive applications. In this study, we focus on a Euro-VI heavy-duty diesel engine, which is equipped with a Waste Heat Recovery system based on an Organic Rankine Cycle. The applied model, which combines first principle modeling with stationary component models, covers the two-phase flow behavior and the effect of control inputs. Furthermore, it describes the interaction with the engine on both gas and drivetrain side. Using engine dynamometer measurements, an optimal fit of unknown model parameters is determined for stationary operating points.

This paper presents a model-based control and calibration design method for online cost-based optimization of engine-aftertreatment operation under all operating conditions. The so-called Integrated Emission Management (IEM) strategy online minimizes the fuel and AbBlue consumption. Based on the actual state of engine and aftertreatment systems, optimal air management settings are determined for EGR-SCR balancing. Following a model-based approach, the strategy allows for a systematic control design and calibration procedure for engine and aftertreatment systems. The potential of this time efficient method is demonstrated by experiments for a heavy-duty Euro-VI engine. The Integrated Emission Management strategy is developed and calibrated offline over a cold and hot World Harmonized Transient Cycle (WHTC) for the set emission targets. The total IEM development and calibration process takes approximately 20 weeks from model identification to the acceptance tests.

This paper presents the first results of an experimental study into a hybrid combustion concept for next-generation heavy-duty diesel engines. In this hybrid concept, at low load operating conditions, the engine is run in Pre-mixed Charge Compression Ignition (PCCI) mode, whereas at high load conventional CI combustion is applied. This study was done with standard diesel fuel on a flexible multi-cylinder heavy-duty test platform. This platform is based on a 12.9-liter, 390 kW heavy-duty diesel engine that is equipped with a combination of a supercharger, a two-stage turbocharging system and low-pressure and high-pressure EGR circuitry. Furthermore, Variable Valve Actuation (VVA) hardware is installed to have sufficient control authority. Dedicated pistons, injector nozzles and VVA cam were selected to enable PCCI combustion for a late DI injection strategy, free of wall-wetting problems.

A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of the exhaust gas aftertreatment system. Following a model-based approach, Integrated Emission Management offers a framework for future control strategy development. This approach alleviates calibration complexity, since it allows to make optimal trade-offs in an operational cost sense. The potential of the presented cost-optimal control strategy is demonstrated for a modern heavy-duty Euro VI engine. The studied diesel engine is equipped with cooled EGR, Variable Geometry Turbocharger, and a DPF-SCR aftertreatment system.

This paper presents a cylinder pressure-based control (CPBC) system for conventional diesel combustion with high EGR levels. Besides the commonly applied heat release estimation, the CPBC system is extended with a new virtual NOx and PM sensor. Using available cylinder pressure information, these emissions are estimated using a physically based combustion model. This opens the route to advanced On-Board Diagnostics and to optimized fuel consumption and emissions during all operating conditions. The potential of closed-loop CA50 and IMEP control is demonstrated on a multi-cylinder heavy-duty EGR engine. For uncalibrated injectors and fuel variations, the combustion control system makes the engine performance robust for the applied variations and reduces the need for a time-consuming calibration process. Cylinder balancing is shown to enable auto-calibration of fuel injectors and to enhance fuel flexibility.

A promising SCR-only solution is presented to meet post-2010 NOx emission targets for heavy duty applications. The proposed concept is based on an engine from a EURO IV SCR application, which is considered optimal with respect to fuel economy and costs. The addition of advanced SCR after treatment comprising a standard and a close-coupled SCR catalyst offers a feasible emission solution, especially suited for EURO VI. In this paper, results of a simulation study are presented. This study concentrates on optimizing SCR deNOx performance. Simulation results of cold start FTP and WHTC test cycles are presented to demonstrate the potential of the close-coupled SCR concept. Comparison with measured engine out emissions of an EGR engine shows that a close-coupled SCR catalyst potentially has NOx reduction performance as good as EGR. Practical issues regarding the use of an SCR catalyst in close-coupled position will be addressed, as well as engine and exhaust layout.

A computationally efficient engine model is developed based on an extended NO emission model and state-of-the-art soot model. The model predicts exhaust NO and soot emission for both conventional and advanced, high-EGR (up to 50 %), heavy-duty DI diesel combustion. Modeling activities have aimed at limiting the computational effort while maintaining a sound physical/chemical basis. The main inputs to the model are the fuel injection rate profile, in-cylinder pressure data and trapped in-cylinder conditions together with basic fuel spray information. Obtaining accurate values for these inputs is part of the model validation process which is thoroughly described. Modeling results are compared with single-cylinder as well as multi-cylinder heavy-duty diesel engine data. NO and soot level predictions show good agreement with measurement data for conventional and high-EGR combustion with conventional timing.

Reaching EUROVI Heavy Duty emission limits will result in more testing time for developing control and OBD algorithms than to reach EUROV emissions. It is likely that these algorithms have to be adapted for a WHTC (World Heavy Duty Transient Cycle) for EUROVI. This cycle when started cold can only be performed a limited times a day on the engine testbench, because of the cooling down time. The development time and cost increases to reach EUROVI emission levels. Accurate simulation tools can reduce the time and costs by reducing the amount of tests required on the testbench. In order to use simulation tools to develop pre calibrations, the models must be fitted and validated. This paper will focus on the fit process of an SCR (Selective Catalytic Reduction) model. A unique test procedure has been developed to characterize an SCR catalyst using an engine testbench in ±2 days. This data is used in an automatic SCR fit tool to obtain the model parameters in a few days.

Selective Catalytic Reduction (SCR) is the dominant solution for meeting future NOx reduction regulations for heavy-duty diesel powertrains. SCR systems benefit from closed-loop control if an appropriate exhaust gas sensor were available. An ammonia sensor has recently been developed for use as a feedback element in closed-loop control of urea dosing in a diesel SCR aftertreatment system. Closed-loop control of SCR dosing enables the SCR system to be robust against disturbances and to meet conformity of production (COP) and in-use compliance norms. The ammonia sensor is based on a non-equilibrium electrochemical principle and outputs emf signals. The sensor performs well when tested in a diesel engine exhaust environment and has minimum cross interference with CO, HC, NO, NO2, SO2, H2O and O2. Previous work, done in a simulation environment, demonstrated that an ammonia sensor provides the optimal feedback for urea dosing control algorithms in closed-loop SCR systems.