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Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

The topology of an EDS, defined by the routing paths and by the location of the distribution boxes and the inline connectors, has a strong impact on weight and required amount of material, especially of copper, as well as on the manufacturing- and assembly time. Although a good part of the routing and packaging is fixed due to technical reasons and carry-over situations, in general there are enough optional paths and locations to allow up to several thousand alternative topologies. For these reasons, an optimization is possible as well as important. For such an optimization, in this paper a method is presented to concurrently minimize predefined criteria, e.g. the required copper, length of the wires, and the overall length of the wire bundles. It is based on designated algorithms for the variation of the topology, the routing, and the calculation of the optimization criteria as mentioned above.

Regulated emissions, CO2-values, comfort, good driveability, high reliability and costs, this is the main frame for all future powertrain developments. In this frame, the diesel powertrain, not only for passenger cars, but also for commercial vehicle applications, faces some challenges in order to fulfil the future European and current US emission legislations while keeping the fuel consumption benefit, good driveability and an acceptable cost frame. One of these challenges is the varying fuel qualities of diesel fuel in different countries including different cetane number, volatility, sulphur content and different molecular composition. In addition to that in the future, more and more alternative fuels with various fuel qualities and properties will be launched into the market for economical and environmental reasons. At present, the control algorithms of the injection system applied in most diesel engines is open loop control.

Controlled Auto Ignition (CAI) as a promising future combustion process is a concept to strongly reduce fuel consumption as well as NOx emissions. The acceptance and the potential of this combustion process depends on the possible CAI operation range in the engine map and the fuel consumption benefit, as well as the complexity of the variable valve train which is necessary to realize the CAI combustion process. The thermodynamic investigations presented in this paper were done on an engine equipped with an electromechanical valve train (EMVT), featuring Port Fuel Injection (PFI) and direct Injection. They show that the electromechanical valve train is an excellent platform for developing the CAI process. Controlled Auto Ignition has been realized with port fuel injection in a speed range between 1000 and 4500 rpm and in a load range between approximately 1 and 6 bar BMEP (about 5 bar BMEP for pressure gradients lower than 3 bar/°CA) depending on engine speed.

During a thermal regeneration of a Diesel particulate filter (DPF) the temperature inside the DPF may raise above critical thresholds in an uncontrolled way (thermal shock). Especially driving conditions with a comparable low exhaust gas mass flow and high oxygen content like idle speed may create a thermal shock. This paper presents a concept for an ECU software structure to prevent the DPF from reaching improper temperatures and the methodology in order to calibrate this ECU structure. The concept deals in general with a closed-loop control of the exhaust gas air-fuel-ratio during the critical engine operation phases. Those critical operation phases are identified at the engine test bench during “Drop-to-Idle” and “Drop-to-Overrun” experiments. The experiments show that those phases are critical having on the one hand a low exhaust gas mass flow and on the other hand a high oxygen percentage in the exhaust gas.

A new index to evaluate the inherent soot reduction in a diesel-like spray plume is proposed in this study. The index is named “Oxidation Potential Number” and was derived with the help of a computational fluid dynamics (CFD) software. C8 - C16 n-alkanes, 1-alcohols and di-n-ethers were studied with the help of this index over four part load engine operating conditions, representative of a C-class diesel vehicle. The CFD modelling results have shown that C8 molecules feature a higher potentiality to reduce the soot. Thus, C8 molecules were tested in a single cylinder diesel engine over the same operating conditions. In conclusion, the proposed index is compared with the soot engine out emission.

The finite nature and instability of fossil fuel supply has led to an increasing and enduring investigation demand of alternative and regenerative fuels. The Institute for Combustion Engines at the RWTH Aachen University carried out an investigation program to explore the potential of tailor made fuels to reduce engine-out emissions while maintaining engine efficiency and an acceptable noise level. To enable optimum engine performance a range of different hydrocarbons having different fuel properties like cetane number, boiling temperature and different molecular compositions have been investigated. Paraffines and naphthenes were selected in order to better understand the effects of molecular composition and chain length on emissions and performance of an engine that was already optimized for advanced combustion performance. The diesel single-cylinder research engine used in this study will be used to meet Euro 6 emissions limits and beyond.

Increasing shortages of energy resources as well as emission legislation development is increasing the pressure to develop more efficient, environmentally friendly propulsion systems for vehicles. Alternatives such as fuel cell systems or hybrid propulsion are in discussion or have already been introduced. This paper gives a survey on the present technical status of internal combustion engines, hybrid concepts and current fuel cell vehicles. Different solutions will be presented, so that an evaluation of advantages and drawbacks can be given. The further potentials of each concept, as well as combinations of different systems are discussed, and an outlook into the future is given.

Faced with one of the greatest challenges of humanity – climate change – the European Union has set out a strategy to achieve climate neutrality by 2050 as part of the European Green Deal. To date, extensive research has been conducted on the CO2 life cycle analysis of mobile propulsion systems. However, achieving absolute net-zero CO2 emissions requires the adjustment of the relevant key performance indicators for the development of mobile propulsion systems. In this context, research is presented that examines the ecological and economic sustainability impacts of a hydrogen-fueled mild hybrid vehicle, a hydrogen-fueled 48V hybrid vehicle, a methanol-fueled 400V hybrid vehicle, a methanol-to-gasoline-fueled plug-in hybrid vehicle, a battery electric vehicle, and a fuel cell electric vehicle. For this purpose, a combined Life-Cycle Assessment (LCA) and Life-Cycle Cost Assessment was performed for the different propulsion concepts.

This article discusses highly flexible and accurate physics-based mean value modeling (MVM) for internal combustion engines and its wide applicability towards virtual vehicle calibration. The requirement to fulfill the challenging Real Driving Emissions (RDE) standards has significantly increased the demand for precise engine models, especially models regarding pollutant emissions and fuel economy. This has led to a large increase in effort required for precise engine modeling and robust model calibration. Two best-practice engine modeling approaches will be introduced here to satisfy these requirements. These are the exclusive MVM approach, and a combination of MVM and a Design of Experiments (DOE) model for heterogeneous multi-domain engine systems.

In the last two decades the abilities of neural networks as universal approximation tools of non linear functional relationships as well as identification tools for nonlinear dynamic systems have been recognized and used successfully in many applications areas like modelling, control and diagnosis of technical systems. At the same time an increasing interest in optimal design methods is observed. Design of experiment is used to cope with the growing amount of measurements needed for the calibration of engines due to the rising number of control variables to be considered and the need for more accuracy in the description of engine behaviour to derive the best control strategies. In this paper a strategy for the integration of the concept of D-optimality in the learning process of neural networks is proposed. This leads to an optimal selection of data to be presented to the training procedure of the neural network aiming to a generation of robust neural models using fewer training data.

The paper presents a simulation environment for the test of driver assistance systems. It covers software-in-the-loop and hardware-in-the-loop test capabilities. In the hardware-in-the-loop (HiL) configuration, real components such as electronic control units (ECUs) and actuators are embedded in the system. First, requirements for a virtual environment are defined. They build the basis for the entire simulation. Special emphasis is given to the interaction between the simulated vehicle under test and its traffic environment. A virtual environment was developed in which the simulated vehicle can drive on a road together with the surrounding traffic. The simulation environment is composed mainly of a traffic scenario generator and a simulation of sensor behavior allowing the recognition of the vehicle's surroundings. Appropriate critical traffic scenarios are generated depending on the tested driver assistance system.

Knock control is one of the most vital functions for safe and fuel-efficient operation of gasoline engines. However, all knock control strategies rely on accurate knock detection to operate the engine close to the optimal set point. Knock detection is usually calibrated on the engine test bench, requiring the engine to run with knocking combustion in a time-consuming multi-stage campaign. Model-based calibration significantly reduces calibration loops on the test bench. However, this method requires a large effort in building and validating the model, which is often limited by the lack of function documentation, available measurements or hardware representation. As the software models are often not available, function structures vary between manufacturers and sub model functions are often documented as black boxes. Hence, using the model-based approach is not always possible.

In this paper a new approach is presented to evaluate the combustion behaviour of homogeneous gasoline engines by predicting burn delay and -duration in a way which can be obtained under the time constraints of the development process. This is accomplished by means of pure in-cylinder flow simulations without a classical combustion model. The burn delay model is based on the local distribution of the turbulent flow near the spark plug. It features also a methodology to compare different designs regarding combustion stability. The correlation for burn duration uses a turbulent characteristic number that is obtained from the turbulent flow in the combustion chamber together with a model for the turbulent burning velocity. The results show good agreement with the combustion process of the analyzed engines.

Multi-motor powertrain topologies are playing an increasingly important role in the development of heavy duty battery electric trucks due to the changing driving requirements of these vehicles. The use of multiple motors and/or transmissions in a powertrain provides additional degrees of freedom for the energy management. The energy management system (EMS) consist of the gear selection strategy and torque split between the drive motors. The aim of the EMS is thereby to achieve high energy efficiency in motor and regenerative operation, while reducing the number of gear changes to ensure driving comfort. Ongoing research focuses on the energy management system of hybrid electric trucks, where the aim is to optimize the torque split between the combustion engine and the electric motor. In this paper, the EMS for an electric truck is described as a mixed-integer nonlinear control problem. This type of optimal control problem is notoriously difficult to solve.

Due to the complex powertrain layout in hybrid vehicles, different configurations concerning internal combustion engine, electric motor and transmission can be combined - as is demonstrated by currently produced hybrid vehicles ([1], [2]). At the Institute for Combustion Engines (VKA) at RWTH Aachen University a combination of simulation, Design of Experiments (DoE) and numerical optimization methods was used to optimize the combustion engine, the powertrain configuration and the operation strategy in hybrid powertrains. A parametric description allows a variation of the main hybrid parameters. Parallel as well as power-split hybrid powertrain configurations were optimized with regard to minimum fuel consumption in the New European Driving Cycle (NEDC). Besides the definition of the optimum configuration for engine, powertrain and operation strategy this approach offers the possibility to predict the fuel consumption for any modifications of the hybrid powertrains.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

In order to thoroughly investigate and improve the path from biofuel production to combustion, the Cluster of Excellence “Tailor-Made Fuels from Biomass” was installed at RWTH Aachen University in 2007. Since then, a variety of fuel candidates have been investigated. In particular, 2-methyl tetrahydrofurane (2-MTHF) has shown excellent performance w.r.t. the particulate (PM) / NOx trade-off [1]. Unfortunately, the long ignition delay results in increased HC-, CO- and noise emissions. To overcome this problem, the addition of di-n-butylether (DNBE, CN ∼ 100) to 2-MTHF was analyzed. By blending these two in different volumetric shares, the effects of the different mixture formation and combustion characteristics, especially on the HC-, CO- and noise emissions, have been carefully analyzed. In addition, the overall emission performance has been compared to EN590 diesel.

Both the rising number of electrical systems and the electrical part of the powertrain are considerably increasing the electrical power requirements of vehicles. As a consequence, multiple voltage supply levels have been introduced. However, even if only the 12V/48V configuration is considered, as in this paper, the number of possible electrical distribution system (EDS) architectures is greatly enlarged. Additional degrees of freedom are the allocation of the loads to the voltage levels, the dimensioning of new components, and the control strategy. Hence, the optimization of such architectures must be based on simulation, which allows the evaluation of a multitude of variants and test scenarios within an acceptable time frame. While strict cost, weight, and quality constraints must be upheld, the stability of the voltage supply is a major focus because a significant part of future electrical systems is highly safety-critical.

The current and future restrictions on pollutant emissions from internal combustion engines require a holistic investigation of the abilities of alternative fuels to optimize the combustion process and ensure cleaner combustion. In this regard, the Tailor-made Fuels from Biomass (TMFB) Cluster at Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen University aims at designing production processes for biofuels as well as fuels optimal for use in internal combustion engines. The TMFB Cluster's scientific approach considers the molecular structure of the fuels as an additional degree of freedom for the optimization of both the production pathways and the combustion process of such novel biofuels. Thus, the model-based specification of target parameters is of the utmost importance to improve engine combustion performance and to send feedback information to the biofuel production process.