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This paper presents a methodology and tool that stochastically generates drive cycles based on measured data, with the purpose of testing and benchmarking light duty vehicles in a simulation environment or on a test-bench. The WLTP database, containing real world driving measurements, was used as input data. Consequently cycles that contain typical accelerations per velocity and road types are generated, such that these cycles are representative to real driving behavior. The stochastic drive cycle generator is developed in Matlab and is based on Markov processes. Two separate stochastic generators are used: one for generating the road type and one for generating the vehicle acceleration. First, a random road type profile is generated from the four different road types that are considered in the WLTP database: urban, rural, motorway and high-motorway, each of them with sub-road types based on different velocity bins.

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.

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.

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.

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.

The goal of this work was to investigate the possibilities of applying high EGR rates with low NOx and PM emission levels on a two-stage turbocharged 12 liter heavy duty diesel engine. The EGR is applied by using a long and short route EGR system. For the ESC operating points A25 and C100 EGR is applied, such that the NOx emission is 0.5 g/kWh. Lowest PM level and BSFC are achieved when long route EGR is applied in A25 and short route is applied in C100. Increasing the fuel line pressure is an effective way to reduce PM at high EGR rate engine running conditions. At a fuel line pressure of 2400 bar PM emission are 0.06 g/kWh for A25 and 0.54 g/kWh for C100. At C100 the PM reduction coincides with also a significant fuel consumption improvement. Retarding the injection timing at C100 can improve the PM emission further to a level of 0.13 g/kWh at the expense of an increase in BSFC.

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.

Up to now, reduction of fuel consumption of vehicles equipped with CVT transmission has not been exploited to its full potential due to the reduced driveability when driving the optimum efficiency engine operating points. An ISG system with torque boost capabilities can be used to restore this driveability. This paper discusses the goals, the CAE simulation tool, the methodology used in the preparative study for evaluation and dimensioning of a CVT-ISG concept, as well as the simulation results. The conclusions, generated from numerous simulations, provide vital information for the component selection, and for the development of the powertrain management system.

The importance of automotive comfort is increasing, both socially and economically. Especially professional drivers often have comfort-related physical complaints, such as lower back pain. In addition, car manufacturers can use comfort to distinguish their cars from their competitors. However, the development and design of a new, more comfortable car seat is very time consuming and costly. The use of computer models of human and seat could facilitate this process. MADYMO human and seat models offer the possibility to predict comfort. This paper describes the application of the MADYMO multi-body 50th percentile human model for determination of human-seat interaction in vertical vibrations. The validation of the human model is based on volunteer tests with both a rigid seat and a standard car seat. The human model shows a good correlation with the volunteers.

Increasing efforts to minimize global warming has led to regulation of greenhouse gas (GHG) emissions of automotive applications. The US is frontrunner regarding implementation of GHG related legislation with the introduction of GHG phase 1 and phase 2, ultimately targeting a 40% fuel consumption reduction in 2027 compared to 2010 on vehicle level. More specific, engines are required to reduce CO2 emissions by 6% compared to GHG phase 1 levels. Next to the GHG emission legislation, more stringent legislation is anticipated in the US to further reduce NOx emissions: a further 90% reduction is targeted as soon as 2024 compared to 2010 standard. Meeting these anticipated ultra-low NOx standards within the GHG phase 2 constraints on CO2 poses a great challenge. This paper presents an overview of the main challenges and key aspects regarding meeting ultra-low NOx requirements within the constraints on CO2 and N2O set by GHG phase 2 regulations.

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 introduction of a new comfortable car seat or interior is a time consuming and costly process for car and seat manufacturers. The application of numerical models of human and seat could facilitate this process. Vertical vibrations and seat pressure distributions are two objective parameters that have been related to the subjective feeling of (dis)comfort that can be predicted by numerical tools. In this paper, human models suitable for prediction of human behaviour in vertical vibrations and seat pressure distributions are applied in a seat sensitivity study. The objective of this paper is to evaluate the applicability of the human models as design tools for car and seat developers in an early stage of the design process. The sensitivity of the output of the models for variations in seat characteristics for seat developers in the design process of a new comfortable car seat has been studied.

Injuries to the knee-thigh-hip (KTH) complex in frontal motor vehicle crashes are of substantial concern because of their frequency and potential to result in long-term disability. Current frontal impact Anthropometric Test Dummies (ATDs) have been shown to respond differently than human cadavers under frontal knee impact loading and consequently current ATDs (and FE models thereof) may lack the biofidelity needed to predict the incidence of knee, thigh, and hip injuries in frontal crashes. These concerns demand an efficient and biofidelic tool to evaluate the occurrence of injuries as a result of KTH loading in frontal crashes. The MADYMO human finite element (FE) model was therefore adapted to simulate bone deformation, articulating joints and soft tissue behavior in the KTH complex.

Interaction of the human arm and deploying airbag has been studied in the laboratory using post mortem human subjects (PMHS). These studies have shown how arm position on the steering wheel and proximity to the airbag prior to deployment can influence the risk of forearm bone fractures. Most of these studies used older driver airbag modules that have been supplanted by advanced airbag technology. In addition, new numerical human body models have been developed to complement, and possibly replace, the human testing needed to evaluate new airbag technology. The objective of this study is to use a finite element-based numerical (MADYMO) model, representing the human arm, to evaluate the effects of advanced driver airbag parameters on the injury potential to the bones of the forearm. The paper shows how the model is correlated to Average Distal Forearm Speed (ADFS) and arm kinematics from two PMHS tests.

Two of the main design objectives for car interiors are comfort and safety. These aspects are both determined by the seating position of the occupant. Seat manufacturers use the SAE Three-Dimensional H-Point Machine™ to measure seating positions to design, audit, and benchmark seats. The seating positions measured with the H-Point Machine form the basis of a seat design, including comfort and safety aspects. Currently, the seat design process is largely based on prototype testing, which makes this process time-consuming and expensive. Consequently, there is a large demand for efficient design tools that enable an optimal combination of seating comfort and safety aspects. Numerical modeling provides an efficient means to optimally combine various seat design characteristics prior to prototype testing, thereby reducing design costs and time-to-market.

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.

Pedestrians and cyclists are the most unprotected road users and their injury risk in case of accidents is significantly higher than for other road users. The understanding of the influence and sensitivity between important variables describing a pedestrian crash is key for the development of more efficient and reliable safety systems. This paper reflects the related work carried out within the AsPeCSS project. The results summarized out of virtual and physical tests provide valuable information for further development. 1168 virtual and 120 physical tests were carried out with adult and child pedestrian headform as well as upper and lower legform impactors representatives of 4 different vehicle front geometries in a wide range of impact speeds, angles and locations. This test matrix was based on previous work carried out within the AsPeCSS project.

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.

Six European laboratories have evaluated the biomechanical response of the new advanced frontal impact dummy THOR-alpha with respect to the European impact response requirements. The results indicated that for many of the body regions (e.g., shoulder, spine, thorax, femur/knee) the THOR-alpha response was close to the human response. In addition, the durability, repeatability and sensitivity for some dummy regions have been evaluated. Based on the tests performed, it was found that the THOR-alpha is not durable enough. The lack in robustness of the THOR-alpha caused a problem in completing the full test program and in evaluating the repeatability of the dummy. The results have demonstrated that the assessment of frontal impact protection can be greatly improved with a more advanced frontal impact dummy. Regarding biofidelity and injury assessment capabilities, the THOR-alpha is a good candidate however it needs to be brought up to standard in other areas.