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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.

To meet future emission targets, it becomes increasingly important to optimize the synergy between engine and aftertreatment system. By using an integrated control approach minimal fluid (fuel and DEF) consumption is targeted within the constraints of emission legislation during real-world operation. In such concept, the on-line availability of engine-out NOx emission is crucial. Here, the use of a Virtual NOx sensor can be of great added-value. Virtual sensing enables more direct and robust emission control allowing, for example, engine-out NOx determination during conditions in which the hardware sensor is not available, such as cold start conditions. Furthermore, with use of the virtual sensor, the engine control strategy can be directly based on NOx emission data, resulting in reduced response time and improved transient emission control. This paper presents the development and on-line implementation of a Virtual NOx sensor, using in-cylinder pressure as main input.

This paper focusses on the application of bioalcohols (ethanol and butanol) derived from seaweed in Heavy-Duty (HD) Compression Ignition (CI) combustion engines. Seaweed-based fuels do not claim land and are not in competition with the food chain. Currently, the application of high octane bioalcohols is limited to Spark Ignition (SI) engines. The Reactivity Controlled Compression Ignition (RCCI) combustion concept allows the use of these low carbon fuels in CI engines which have higher efficiencies associated with them than SI engines. This contributes to the reduction of tailpipe CO2 emissions as required by (future) legislation and reducing fuel consumption, i.e. Total-Cost-of-Ownership (TCO). Furthermore, it opens the HD transport market for these low carbon bioalcohol fuels from a novel sustainable biomass source. In this paper, both the production of seaweed-based fuels and the application of these fuels in CI engines is discussed.

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.

Complying to both the increasingly stringent pollutant emissions as well as (future) GHG emission legislation - with increased focus on in-use real-world emissions - puts a great challenge to the engine/aftertreatment control development process. Control system complexity, calibration and validation effort has increased dramatically over the past decade. A trend that is likely to continue considering the next steps in emission and GHG emission legislation. Control-oriented engine models are valuable tools for efficient development of engine monitoring and control systems. Furthermore, these (predictive) engine models are more and more used as part of control algorithms to ensure legislation compliant and optimized performance over the system lifetime. For these engine models, it is essential that simulation and prediction of system variables during non-nominal engine operation, such as non-standard ambient conditions, is well captured.