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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.

This paper describes an approach to reduce development costs and time by frontloading of engineering tasks and even starting calibration tasks already in the early component conception phases of a vehicle development program. To realize this, the application of a consistent and parallel virtual development and calibration methodology is required. The interaction between vehicle subcomponents physically available and those only virtually available at that time, is achieved with the introduction of highly accurate real-time models on closed-loop co-simulation platforms (HiL-simulators) which provide the appropriate response of the hardware components. This paper presents results of a heterogeneous testing scenario containing a real internal combustion engine on a test facility and a purely virtual vehicle using two different automatic transmission calibration and hardware setups.

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.

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.

Plug-In Hybrid Vehicles (PHEV) have been of significant importance recently to comply with future CO2 and pollutant emissions limit. However, performance of these vehicles is closely related to the energy management strategy (EMS) used to ensure minimum fuel consumption and maximize electric driving range. While conventional EMS concepts are developed to operate in wide range of scenarios, this approach could potentially compromise the fuel consumption benefit due to the omission of route and traffic information. With the advancements in the availability of real-time traffic, navigation and driving route information, the EMS can be further optimized to extract the complete potential of a PHEV. In this context, this paper presents application of predictive energy management (PEM) functionalities combined with information such as live traffic data to reduce the fuel consumption for a P1/P3 configuration PHEV vehicle.

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.

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.

Most of today’s internal combustion engines are turbocharged by combined radial compressors and turbines for downsizing. This mostly leads to reduced orifice noise of both intake and exhaust systems, but the detailed damping mechanisms remain yet unknown. Intake and exhaust systems are developed with 1D-CFD simulations, but validated acoustic sub-models for turbochargers are not yet available. Therefore the aim of this publication is studying the turbocharger’s silencing capabilities and subsequently develop new acoustic turbocharger models. The acoustic properties of the turbocharger can be well described by transmission loss. In addition to thermodynamic variations, parameter variations with wastegate and VTG systems were also performed. A total of four turbochargers of very different sizes were investigated. Low frequency attenuation is dominated by impedance discontinuities, increasing considerably with mass flow and pressure ratio.

To achieve global market and brand specific drivability characteristics as unique selling proposition for the increasing number of passenger car derivatives, an objectified evaluation approach for the drivability capabilities of the various cars is required. Thereto, it is necessary to evaluate the influence of different engine concepts in various complex and interlinked powertrain topologies during engine load change maneuvers based on physical criteria. Such an objectification approach enables frontloading of drivability related engineering tasks by the execution of drivability development and calibration work within vehicle subcomponent-specific closed-loop real-time co-simulation environments in early phases of a vehicle development program. So far, drivability functionalities could be developed and calibrated only towards the end of a vehicle development program, when test vehicles with a sufficient level of product maturity became available.

Numerical analyses of the liquid fuel injection and subsequent fuel-air mixing for a high-tumble direct injection engine with an active pre-chamber ignition system at operation conditions of 2000 RPM are presented. The Navier-Stokes equations for compressible in-cylinder flow are solved numerically using a hierarchical Cartesian mesh based finite-volume method. To determine the fuel vapor before ignition large-eddy flow simulations are two-way coupled with the spray droplets in a Lagrangian Particle Tracking (LPT) formulation. The combined hierarchical Cartesian mesh ensures efficient usage of high performance computing systems through solution adaptive refinement and dynamic load balancing. Computational meshes with approximately 170 million cells and 1.0 million spray parcels are used for the simulations.

Maintaining low NOx emissions over the operating range of diesel engines continues to be a major issue. However, optical measurements of nitric oxide (NO) are lacking particularly in the core of diesel jets, i.e. in the region of premixed combustion close to the spray axis. This is basically caused by severe attenuation of both the laser light and fluorescent emission in laser-induced fluorescence (LIF) applications. Light extinction is reduced by keeping absorption path lengths relatively short in this work, by investigating diesel jets in a combustion vessel instead of an engine. Furthermore, the NO-detection threshold is improved by conducting 1-d line measurements instead of 2-d imaging. The NO-LIF data are corrected for light attenuation by combined LIF and spontaneous Raman scattering. The quantified maximum light attenuation is significantly lower than in comparable previous works, and its wavelength dependence is surprisingly weak.

Compliance with the future CO2 emission limits for the fleet of vehicles sold presents a major challenge for the automotive industry. To comply with these stringent limits, one solution is mobility using hydrogen as an energy carrier. In this context, the development of Proton Exchange Membrane (PEM) fuel cells for commercial vehicle applications, both on- and off-road, is of significant interest due to the non-existent CO2 emissions. However, performance of these devices is closely related to the control concepts that are used to ensure high efficiency, good transient performance, high reliability & durability as well as safe operation. To address these challenges, this paper presents a modular Fuel Cell Control Software which offers the potential to be used for different P&ID (Piping & Instrumentation Diagram) configurations of fuel cell systems.

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with reduced development times. The growing number of vehicle variants, sharing similar engines and control algorithms, requires different calibrations. Additionally, these engines feature an increasing number of calibration parameters, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art logic-level (white box) model-based calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited functional documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (black box) for two distinct ECU functional structures with minimal software documentation.

In this work, a transport and mixing model that calculates mixing in thermodynamic phase space was derived and validated. The mixing in thermodynamic multizone space is consistent to the one in the spatially resolved physical space. The model is developed using a turbulent channel flow as simplified domain. This physical domain of a direct numerical simulation (DNS) is divided into zones based on the quantitative value of transported scalars. Fluxes between the zones are introduced to describe mixing from the transport equation of the probability density function based on the mixing process in physical space. The mixing process of further scalars can then be carried out with these fluxes instead of solving additional transport equations. The relationship between the exchange flux in phase space and the concept of scalar dissipation are shown and validated by comparison to DNS results.

With increasing interest in new biofuel candidates, 1-octanol and di-n-butylether (DNBE) were presented in recent studies. Although these molecular species are isomers, their properties are substantially different. In contrast to DNBE, 1-octanol is almost a gasoline-type fuel in terms of its auto-ignition quality. Thus, there are problems associated with engine start-up for neat 1-octanol. In order to find a suitable glow-plug position, mixture formation is studied in the cylinder under almost idle operating conditions in the present work. This is conducted by planar laser-induced fluorescence in a high-speed direct-injection optical diesel engine. The investigated C8-oxygenates are also significantly different in terms of their evaporation characteristics. Thus, in-cylinder mixture formation of these two species is compared in this work, allowing conclusions on combustion behavior and exhaust emissions.