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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.

Wet clutch friction performance has historically been visualized by multiple graphs due to the number of temperatures and pressures required to characterize the system. However, this same friction performance can be visualized by a single graph using an alternative approach to map the friction data. Applying a method similar to that used to develop the Stribeck curve for journal bearings, a single system-level graph for wet clutches can be created. This paper will highlight how this visualization method, particularly when used to diagnose clutch failures, provides benefits in understanding the effects of both the friction material and the lubricant performance. We conducted extensive studies comparing ideal clutch systems with failed ones under a variety of conditions. Lubricant and friction material failures were independently studied, and durability tests were conducted to evaluate component failures.

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.

Increasingly stringent vehicle emissions legislation is being introduced throughout the world, regulating the allowed levels of particulate matter emitted from vehicle tailpipes. The regulation may prove challenging for gasoline vehicles equipped with modern gasoline direct injection (GDI) technology, owing to their increased levels of particulate matter production. It is expected that gasoline particulate filters (GPFs) will soon be fitted to most vehicles sold in China and Europe, allowing for carbonaceous particulate matter to be effectively captured. However, GPFs will also capture and accumulate non-combustible inorganic ash within them, mainly derived from engine oil. Studies exist to demonstrate the impact of such ash on GPF and vehicle performance, but these commonly make use of accelerated ash loading methods, which themselves introduce significant variation.

With the adoption of the Worldwide harmonized Light Vehicles Test Procedure (WLTP) and the Real Driving Emissions (RDE) regulations for testing and monitoring the vehicle pollutant emissions, as well as CO2 and fuel consumption, the gap between real world and type approval performances is expected to decrease to a large extent. With respect to CO2, however, WLTP is not expected to fully eliminate the reported 40% discrepancy between real world and type approval values. This is mainly attributed to the fact that laboratory tests take place under average controlled conditions that do not fully replicate the environmental and traffic conditions experienced over daily driving across Europe. In addition, any uncertainties of a pre-defined test protocol and the vehicle operation can be optimized to lower the CO2 emissions of the type approval test. Such issues can be minimized in principle with the adoption of a real-world test for fuel consumption.

The Reactivity Controlled Compression Ignition concept for dual-fuel engines has multiple challenges of which some can be overcome using Variable Valve Actuation approaches. For various fuel combinations, the engine research community has shown that running dual-fuel engines in RCCI mode, improves thermal efficiency and results in ultra-low engine-out nitrous oxides and soot. However, stable RCCI combustion is limited to a certain load range, depending on available hardware. At low loads, the combustion efficiency can drop significantly, whereas at high loads, the maximum in-cylinder pressure can easily exceed the engine design limit. In this paper, three VVA measures to increase load range, improve combustion efficiency, and perform thermal management are presented. Simulation results are used to demonstrate the potential of these VVA measures for a heavy-duty engine running on natural gas and diesel.

Seat assessment is an important necessity for the growing auto industry. The design of seats is driven by customer’s demand of comfort and aesthetics of the vehicle interiors. Some of the few seat assessments are H-point prediction with H-point Machine (HPM); backset prediction with Head Restraint Measuring Device (HRMD); seat hardness and softness. Traditional seat development was through developing series of prototypes to meet requirements which involved higher costs and more time. The seat requirement of H-Point measurement is of focus in this paper. Though there are other commercial available software/methods to perform the H-point measurement simulations, the aim here was to assess the capabilities of an alternate Computer Aided Engineering (CAE) methodology using CAE tools - PRIMER and LS-Dyna. The pre-processing tools - Hypermesh and ANSA have been used for modeling and Hyperview tool used for reviewing the simulations.

Downsized gasoline engines, coupled with gasoline direct injection (GDI) and turbocharging, have provided an effective means to meet both emissions standards and customers’ drivability expectations. As a result, these engines have become more and more common in the passenger vehicle marketplace over the past 10 years. To maximize fuel economy, these engines are commonly calibrated to operate at low speeds and high engine loads – well into the traditional ‘knock-limited’ region. Advanced engine controls and GDI have effectively suppressed knock and allowed the engines to operate in this high efficiency region more often than was historically possible. Unfortunately, many of these downsized, boosted engines have experienced a different type of uncontrolled combustion. This combustion occurs when the engine is operating under high load and low speed conditions and has been named Low Speed Pre-Ignition (LSPI). LSPI has shown to be very damaging to engine hardware.

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.

SCR on Filter (SCRoF) is an efficient and compact NOX and PM reduction technology already used in series production for light-duty applications. The technology is now finding its way into the medium duty and heavy duty market. One of the key challenges for successful application is the robustness to real world variations. The solution to this challenge can be found by using model-based control algorithms, utilizing state estimation by physics-based catalyst models. This paper focuses on the development, validation and real time implementation of a physics-based control oriented SCRoF model. An overview of the developed model will be presented, together with a brief description of the model parameter identification and validation process using engine test bench measurement data. The model parameters are identified following a streamlined approach, focusing on decoupling the effects of deNOx and soot phenomena.

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.

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.

The next generation off-road vehicles will see additional exhaust gas aftertreatment systems, ranging from DOC-SCR only to full DOC-DPF-SCR-AMOX systems. This will increase system complexity and development effort significantly. Emission requirements and the high number of vehicle configurations within the off-road industry will require a new process for development and validation. The introduced model-based approach using physical models of aftertreatment can reduce development effort and cost, improve performance robustness and help to identify performance issues early in the development process. A method to investigate and optimize a large matrix of variations by simulation is introduced. This can lead to a significant reduction in the number of required calibrations and can assist in the development of design specifications for the aftertreatment system. A case study for SCR calibration successfully demonstrates the potential of model-based development.

A virtual diesel aftertreatment exhaust line is presented comprising DOC, DPF, SCR models and a unique Ammonia Oxidation catalyst model. All models are one dimensional models based on first principles. These models offer an attractive compromise between speed, accuracy and complexity for a variety of model applications: off-line simulation, control strategy development, Hardware in the Loop applications and model-based calibration. The implemented models are fast and suitable for real-time applications. Use of these virtual exhaust line models in a product development process has the potential of saving time and resources. The aftertreatment models are fitted based on specifically designed engine dynamometer experiments, which can be performed in a limited time frame. The effective test time required on a validated test setup is estimated on the order of 12 days in total. Specifically developed software tools facilitate the model fit process.

Two major trends can be identified for powertrain control in the next decade. The legislation will more and more focus on in-use emissions. Together with the global trend to reduce the CO₂ emissions, this will lead to an integral drive train approach. To develop and validate this integral drive train approach, the need for a new chapter in powertrain testing arises. The climatic-altitude chamber, suited for heavy vehicles, serves a wide variety of testing needs. Ambient temperature can be controlled between -45°C and +55°C and ambient pressure can be reduced up to a level found at an altitude to 4000 meters. The chamber's dynamometers enable transient testing of heavy-duty engines and vehicles and the chamber is equipped with a comprehensive array of emission measurement capabilities, working under extreme conditions.

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.

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.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.