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Integrated Emission Management (IEM) is a supervisory control strategy that aims at minimizing the operational costs of diesel engines with an aftertreatment system, while satisfying emission constraints imposed by legislation. In previous work on IEM, a suboptimal real-time implementable solution was proposed, which was based on Pontryagin's Minimum Principle (PMP). In this paper, we compute the optimal solution using Dynamic Programming (DP). As the emission legislation imposes a terminal state constraint, standard DP algorithms are sensitive to numerical errors that appear close to the boundary of the backward reachable sets. To avoid these numerical errors, we propose Boundary Surface Dynamic Programming (BSDP), which is an extension to Boundary Line Dynamic Programming and uses an approximation of the backward reachable sets. We also make an approximation of the forward reachable sets to reduce the grid size over time. Using a simulation study of a cold-start World Harmonized Transient Cycle for a Euro VI engine, we show that BSDP results in the best approximation of the optimal cost, when compared to existing DP methods, and that the real-time implementable solution only deviates 0.16 [%] from the optimal cost obtained using BSDP. cop. IFAC.

This study discusses the model of operation of a dual-fuel compression-ignition engine, powered by gaseous fuel with an initial dose of diesel fuel as the ignition inhibitor. The study used a zero-dimensional multiphase mathematical model of a dual-fuel engine to simulate the impact of enhancing Natural Gas (NG) with other gases on the combustion process. The model simulated the thermodynamic parameters of the gas mixture in the cylinder of a dual-fuel (NG/Diesel), turbocharged, four cylinder CRDI (Common-Rail Direct Injection) engine. The tests discussed herein were conducted for steady state engine operation, for partial load and constant consumption of gaseous fuel. In the discussed tests, carbon dioxide and higher hydrocarbons (ethane and propane) were used as additions to NG.It has been shown that a change of gas composition has a significant impact on the combustion process and parameters of operation of a dual-fuel engine. The combustion of gas additives largely determines the combustion of both the main component of gaseous fuel and the initial dose of diesel fuel. The addition of higher hydrocarbons to methane can improve engine performance by as much as 6% with additions of higher carbon amounting to 20% of total fuel volume. Also, it has been shown that changes of gas composition significantly impact the ignition delay of the initial diesel dose. cop. 2016 Elsevier B.V.

With the application of multiple-pulse fuel injection profiles, the performance of diesel engines is enhanced in terms of low fuel consumption and low engine-out emission levels. However, the calibration effort increases due to a larger number of injection timing parameters. The difficulty of controlling the combustion phase also increases because of coupling between individual fuel injection pulses. In the pursuit of more efficient diesel engines, each fuel injection pulse needs to be optimised and actively controlled against component ageing, ambient condition changes and fuel variations. This paper presents an off-line method to compute the optimal multiplepulse fuel injection profile with explicit considerations of both torque output and engine-out emission requirements. A multiinput multi-output feedback controller is designed to regulate the entire fuel injection profile against disturbances. Numerical simulation results are given based on a heavy-duty truck engine model.

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. A simulation study shows that the proposed Integrated Emission Management strategy accomplishes 2% to 3% reduction in fuel consumption and operating costs compared to a baseline strategy. Further potential benefits include reduced heat rejection associated with the EGR system and reduced DPF regeneration frequency. © 2011 SAE International.

Energy management in hybrid vehicles typically relates to the vehicle powertrain, whereas emission management is associated with the combustion engine and aftertreatment system. To achieve maximum performance in fuel economy and regulated pollutants, the concept of (model-based) Integrated Powertrain Control (IPC) is proposed. Based on results from optimal control and the Equivalent Consumption Minimization Strategy, this paper presents a novel IPC strategy for a series hybrid electric heavy duty vehicle with a SCR (Selective Catalytic Reduction) DeNOx aftertreatment system. This strategy makes use of a control model incorporating the dynamics of both the powertrain components as well as the aftertreatment system. Simulation results demonstrate how IPC can optimize the classical trade-off between operational costs (comprising fuel use and AdBlue dosing) versus the production of tail-pipe NOx emissions.

This article presents a cost-based optimization strategy that explicitly deals with the requirements for fuel consumption and emissions. Based on the Integrated Powertrain Control (IPC) approach, the overall powertrain performance is optimized by integrated energy and emission management. The potential of this strategy is demonstrated for a parallel hybrid diesel truck with a Selective Catalytic Reduction (SCR) de-NOx system. New results are presented for a challenging city cycle; although the average power demand is low, IPC is able to keep the SCR catalyst temperature relatively high. With this IPC approach, the CO2-NOx trade-off is optimized in a systematic way. It is demonstrated that CO2 emissions and related operating costs are reduced by 3.5% or 24.9% NOx emission reduction is achieved, depending on the applied IPC calibration. Copyright © 2011 by ASME.

This paper presents an on-line model identification method for Li-ion battery parameters that combines high accuracy and low computational complexity. Experimental results show that modeling errors are smaller than 1% throughout the feasible operating range. The identified model is used in a state observer - an Extended Kalman Filter (EKF) - to obtain an indication about the battery State of Charge (SoC). A novel method to estimate the actual battery capacity on-line, based on the data from the state observer is presented. Based on the real battery capacity, an indication about the State of Health (SoH) can be given. Simulation and experimental results are presented to validate the proposed methodology. Battery capacity estimation errors under 4% are achieved by using only 30 minutes of data (battery voltage and current measurements) acquired during normal driving. © 2012 IEEE.

Existing gasoline DI injection equipment has been modified to generate single hole pulsed gas jets. Injection experiments have been performed at combinations of 3 different pressure ratios (2 of which supercritical) respectively 3 different hole geometries (i.e. length to diameter ratios). Injection was into a pressure chamber with optical access. Injection pressures and injector hole geometry were selected to be representative of current and near-future DI natural gas engines. Each injector hole design has been characterized by measuring its discharge coefficient for different Re-levels. Transient jets produced by these injectors have been visualized using planar laser sheet Mie scattering (PLMS). For this the injected gas was seeded with small oil droplets. The corresponding flow field was measured using particle image velocimetry (PIV) laser diagnostics. From the corresponding measurements, both the jet spreading angle and penetration have been determined according to different definitions and the interrelation between these definitions has been examined. Results show that -beyond the initial transition period and almost up to the tip vortex region - (average) jet angle is almost constant. Furthermore, jet penetration is well predicted by correlations that implicitly assume momentum conservation at constant static pressure. Measurements suggest a different time-averaged velocity profile from that typically assumed in some of these correlations. Tip vortex position and size scale with transient jet penetration. © 2010 SAE International.

Binnen, het eind vorig jaar afgelopen, Evident-project hebben onder meer TNO en Tomtom gewerkt aan een intelligent navigatiesysteem voor elektrische voertuigen. Onderdeel hiervan was de ontwikkeling van een algoritme om accuraat te schatten wanneer de accu leeg is. Het resultaat blijkt beter dan de huidige standaard.

This study presents an integrated energy and emission management strategy which minimizes the operational costs over the study test cycle. This Integrated Powertrain Control (IPC) strategy deals with high system complexity and exploits the synergy between engine-aftertreatment systems by following a model-based approach. The potential of this integrated approach is demonstrated for a new application: an Euro-VI diesel engine with Waste Heat Recovery system. Main contribution of this work is to include the emission constraints in the control design for this application. In a simulation study, the performance of the presented IPC strategy is compared with a baseline engine control strategy over the World Harmonized Transient Cycle. It is shown that the IPC strategy explicitly deals with the NOx tailpipe emission target and simultaneously reduces CO2 emissions by 2.8% compared to the baseline strategy.

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 tubocharging system and lowpressure and highpressure EGR circuitry. Furthermore, Variable Valve Actuation (VVA) hardware is installed to have sufficìent control authority. Dedicated pistons, injector nozzles and VVA cam were selected to enable PCCI oombustion for a late DI injection strategy, free of wall-wetting problems. The decision to use a multicylinder configuration instead of a single cylinder research engine was taken because thìs allows to assess the impact of limitations in operating range of current turbocharger equipment and that of cylinder interaction. It also allowed to assess control issues relevant for future production engines. First results are shown for four low load ESC operating points, Injection timing, EGR rate and effective compression ratio are varied to find suitable PCCI operating conditions with this equipment. The effect of these control parameters on combustion phasing, heat release, emissions (NOx, HC, CO, smoke), and fuel consumption is presented. Similar trade-offs are determined for conventional CI combustion at higher loads. From the experimental results, it is concluded that PCCI combustion is succcessfuly realized up to 25% load, corresponding to 5.6 bar BMEP. Further optimization of TC matching and combustion is needed to improve PCCI fuel efficiency and especially high load CI operation.

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 modelling 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. From model validation, it is concluded that the identified model shows good accuracy in steady-state and can reasonably capture the most important dynamics over a wide range of operating conditions. The resulting real-time model is suitable for model-based control. Copyright © 2013 SAE International.

Closed-loop combustion control helps to achieve precise fuel injection and robust engine performance against disturbances. The controller design complexity increases greatly with larger number of fuel injection pulses due to the coupled influence of changing individual pulse on the combustion process. In this work, we experimentally demonstrate the potential of a novel design methodology, which automatically computes a multivariable combustion controller. Using a one-cylinder test bench, we tested a single combustion controller in both the nominal and the disturbed operating condition with varied EGR valve position. The controller shows robust closed-loop stability and fast dynamical performance in both conditions as well as during the transition in between.

This article describes a NOx sensor based urea dosing control strategy for heavy-duty diesel aftertreatment systems using Selective Catalytic Reduction. The dosing control strategy comprises of a fast-response, model-based ammonia storage control system in combination with a long-timescale tailpipe-feedback module that adjusts the dosing quantity according to current aftertreatment conditions. This results in a control system that is robust to system disturbances such as biased NOx sensors and variations in AdBlue concentrations. The cross-sensitivity of the tailpipe NOx sensor to ammonia is handled by a novel, smart signal filter that can reliably identify the contributions of NOx and NH3 in the tailpipe sensor signal, without requiring an artificial perturbation of the dosing signal. The tailpipe feedback module compares the signal from the cross-sensitive tailpipe NOx sensor to the modeled tailpipe sensor signal to estimate the measured and modeled NOx conversion and NH3 slip, without the need for an NH3 sensor. The difference between these measured and modeled quantities is used to adjust the dosing quantity to the aftertreatment system, thereby maintaining nominal performance of the aftertreatment system in the presence of disturbances. Simulation results are presented of the urea dosing control system covering a wide range of disturbances, demonstrating the robustness properties of the controlled system. The robust urea dosing control strategy was implemented on a rapid prototyping platform and tested on a state-of-the-art Euro VI engine and aftertreatment systems, confirming the expected performance and robustness properties.

This report describes the experimental validation of the powertrain models developed in the WP21. The experimental tests consider the dynamical model of the vehicle and also the energy consumption model. The structure of this report is divided into four parts corresponding to the four powertrain configurations described in WP21. Each part covers the powertrain model, its inputs and outputs, and provides an experimental plan with the associated results. The deliverable shows the appropriateness of the simulated powertrain models to the measured signals obtained on the equipped vehicles.

This deliverable provides a description of test scenarios that will be used for validation of WP22’s on-line vehicle algorithms. These algorithms consist of the two modules VE³ (Vehicle Energy and Environment Estimator) and RSG (Reference Signal Genera-tor) and will be tested using the Matlab/Simulink and the macro-scopic simulation framework PELOPS. The applied scenarios are created in order to validate the algorithms with regard to per-formance and robustness and to close the gap between driving cycle simulations and real-world tests.

This deliverable reports on the simulations and analysis of the on-line vehicle algorithms as well as the ecoDriver Android application. The simulation and field test results give an impression of how the algorithms will perform in the real world trials in SP3. Thus, it is possible to apply improvements, if needed, before the full ecoDriver system (consisting of algorithms from SP2 and HMI solutions from SP1) is implemented in the test vehicles.

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 incylinder pressure prediction. The model is validated using NG-diesel RCCI measurements that are performed on a 6 cylinder heavy-duty engine. For three different engine operating points, it is operated at various diesel injection timings and NG-diesel blend ratios. The validation is focused on variables that are relevant for engine control, such as CA50, peak cylinder pressure, and engine-out NOx emissions. The validation shows that the multi-zone method with detailed chemistry reproduces the correct trends for important control parameters. From this validated model, real-time, map-based RCCI models are derived, which are considered to be an important step towards model-based NG-diesel RCCI control development.

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. By combining model predictions of the external load and of the crank angle variations, individual cylinder pressure variations are determined following a signal tracking approach. The potential of this virtual cylinder pressure sensor concept is demonstrated for a six cylinder Diesel engine that operates under transient load conditions. A comparison with experimental data shows that relevant combustion control parameters, such as, CA50 and IMEP can be approximated with ±1.5 [°CA] and ± 0.5 [bar] accuracy, respectively, during transients.

With an increased number of fuel injection pulses, the control problem in diesel engines becomes complex. Consisting of multiple single-input single-output (SISO) controllers, the conventional control strategy shows unsatisfactory dynamic performance in tracking combustion load and phase reference metrics. In this paper, a general framework is discussed that describes the combustion process on a cycle-to-cycle basis with parametrized fueling profiles. It provides a systematic approach for combustion controller design with multi-pulse fuel injection since the correlated inuence of changing individual fuel injection pulses is explicitly considered. Based on a sensitivity analysis, a multi-input multi-output (MIMO) combustion controller is designed with local stability guarantee. It shows faster and decoupled tracking performance compared with the conventional (SISO) combustion controller in a numerical simulation based on a validated engine model.