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The technology used in hybrid vehicle concepts is significantly different from conventional vehicle technology with consequences also for the noise and vibration behavior. In conventional vehicles, certain noise phenomena are masked by the engine noise. In situations where the combustion engine is turned off in hybrid vehicle concepts, these noise components can become dominant and annoying. In hybrid concepts, the driving condition is often decoupled from the operation state of the combustion engine, which leads to unusual and unexpected acoustical behavior. New acoustic phenomena such as magnetic noise due to recuperation occur, caused by new components and driving conditions. The analysis of this recuperation noise by means of interior noise simulation shows, that it is not only induced by the powertrain radiation but also by the noise path via the powertrain mounts. The additional degrees of freedom of the hybrid drive train can also be used to improve the vibrational behavior.

In order to reduce engine out CO2 emissions, it is a main subject to find new alternative fuels from renewable sources. For identifying the specification of an optimized fuel for engine combustion, it is essential to understand the details of combustion and pollutant formation. For obtaining a better understanding of the flame behavior, dynamic structure large eddy simulations are a method of choice. In the investigation presented in this paper, an n-heptane spray flame is simulated under engine relevant conditions starting at a pressure of 50 bar and a temperature of 800 K. Measurements are conducted at a high-pressure vessel with the same conditions. Liquid penetration length is measured with Mie-Scatterlight, gaseous penetration length with Shadowgraphy and lift-off length as well as ignition delay with OH*-Radiation. In addition to these global high-speed measurement techniques, detailed spectroscopic laser measurements are conducted at the n-heptane flame.

One of the challenges faced when using Li-ion batteries in electric vehicles is to keep the cell temperatures below a given threshold. Mathematical modeling would indeed be an efficient tool to test virtually this requirement and accelerate the battery product lifecycle. Moreover, temperature predicting models could potentially be used on-board to decrease the limitations associated with sensor based temperature feedbacks. Accordingly, we present a complete modeling procedure which was used to calculate the cell temperatures during a given electric vehicle trip. The procedure includes a simple vehicle dynamics model, an equivalent circuit battery model, and a 3D finite element thermal model. Model parameters were identified from measurements taken during constant current and pulse current discharge tests. The cell temperatures corresponding to an actual electric vehicle trip were calculated and compared with measured values.

Depending on a vehicles drive cycle, an improvement of the overall drivetrain efficiency does not necessarily have to go along with an improvement of its mileage. In here the ratio of energy to overcome rolling resistance, aerodynamic drag, acceleration and energy wasted directly in wheel brakes is responsible for potentially differing trends. A detailed knowledge of energy flows, sources and sinks makes up a substantial step into optimizing any drive train. Most fuel energy leaves the drivetrain via exhaust pipes. Next to usable mechanical energy, a big amount is spent to heat up the system directly or to overcome drive train friction, which is converted into heat to warm up the system additionally. An in depth quantification of the most important energy flows for an upper middle-sized class gasoline powered drive train is given as results of warm-up cycle simulations.

Modeling thermal systems in Battery Electric Vehicles (BEVs) is crucial for enhancing energy efficiency through predictive control strategies, thereby extending vehicle range. A major obstacle in this modeling is the often limited availability of detailed system information. This research introduces a methodology using neural networks for system identification, a powerful technique capable of approximating the physical behavior of thermal systems with minimal data requirements. By employing black-box models, this approach supports the creation of optimization-based operational strategies, such as Model Predictive Control (MPC) and Reinforcement Learning-based Control (RL). The system identification process is executed using MATLAB Simulink, with virtual training data produced by validated Simulink models to establish the method's feasibility. The neural networks utilized for system identification are implemented in MATLAB code.

One challenge for the development of commercial vehicles is the reduction of CO2 greenhouse, where hydrogen can help to reduce the fleet CO2. For instance, in Europe a drop in fleet consumption of 15% and 30% is set as target by the regulation until 2025 and 2030. Another challenge is EURO VII in EU or even already approved CARB HD Low NOx Regulation in USA, not only for Diesel but also for hydrogen combustion engines. In this study, first the requirements for the combustion and after-treatment system of a hydrogen engine are defined based on future emission regulations. The major advantages regarded to hydrogen combustion are due to the wide range of flammability and very high flame speed numbers compared to other fossil based fuels. Thus, it can be well used for lean burn combustion with much better fuel efficiency and very low NOx emissions with an ultra lean combustion. A comprehensive experimental investigation is performed on a HD 2 L single-cylinder engine.

In this article, the development challenges of a fuel cell system are explained using the example of the BREEZE! fuel cell range extender (FC-REX) applied in an FEV Liiona. The FEV Liiona is a battery electric vehicle based on a Fiat 500 developed by FEV. The BREEZE! system is the first applied 30 kW low temperature polymer electrolyte membrane (LT PEM) fuel cell system in the subcompact vehicle class. Due to the highly integrated system approach and dry cathode operation, a compact design of the range extender module with a system power density of 0.45 kW/l can be achieved so that the vehicle interior including trunk remains completely usable. System development for fuel cells significantly influences performance, efficiency, package, durability, and required maintenance effort of a fuel cell electric powertrain. In order to ensure safe and reliable operation, the fuel cell system has to be supplied with sufficient amounts of air, hydrogen, and coolant flows.

Hybrid and electric vehicles present a promising trade-off between the necessary reductions in emissions and fuel consumption, the improvement in driving pleasure and performance of today's and tomorrow's vehicles. These hybrid vehicles rely primarily on electronics for the control and the coordination of the different sub-systems or components. The number and complexity of the functions distributed over many control units is increasing in these vehicles. Functional safety, defined as absence of unacceptable risk due to the hazards caused by mal-function in the electric or electronic systems is becoming a key factor in the development of modern vehicles such as electric and hybrid vehicles. This important increase in functional safety-related issues has raised the need for the automotive industry to develop its own functional safety standard, ISO 26262.

The newest legislative trends enforce a significant decrease in CO2 emissions for commercial vehicles. For instance, in Europe a drop in fleet consumption of 15% and 30% is set as target by the regulation by 2025 and 2030. The use of carbon-neutral fuels offers possibilities regarding net-zero CO2 emissions - although not yet considered by the rules. Another challenging aspect is the drastic tightening of NOx emissions limits for future legislations, which is approved or being discussed both for the United States and for the EU. The current work describes the potentials of an innovative fuel, marketed as Gane fuel regarding performance, efficiency and emission behavior. First, the properties of the developed fuel are described: Gane is made from methanol blended with water and is tailored for diffusive combustion. The fuel blending is so defined to fulfill the combustion requirements.

Further tightening of NOx emission standards as well as CO2 emission limits for commercial vehicles are currently under discussion. In the on-road market, lowering NOx emissions up to 90%, down to 0.02 g/bhp-hr, has been proposed by CARB and is evaluated by US EPA. Testing for in-service conformity using a portable emission measurement system (PEMS) is currently under review in the US. In Europe, CO2 emission limits are anticipated and a CO2 monitoring program is ongoing. PEMS legislation has been recently tightened and further restrictions can be expected. Stage V legislation has been introduced in Europe and it is foreseeable that further tightening of off-road standards will take place in the future. This study deals with virtual development and evaluation of future engine and exhaust aftertreatment (EAT) technology solutions to fulfill the diverse future emission requirements with emphasis on off-road applications.

The development and calibration of modern combustion engines is challenging in the area of continuously tightening emission limits and the necessity for meeting real driving emissions regulations. A focus is on the knowledge of the internal engine processes and the determination of pollutants formations in order to predict the engine emissions. A physical model-based development provides an insight into hardly measurable phenomena properties and is robust against changing input data. With increasing modeling depth the required computing capacities increase. As an alternative to physical modeling, data-driven machine learning methods can be used to enable high-performance modeling accuracy. However, these are dependent on the learned data. To combine the performance and robustness of both types of modeling a hybrid application of data-driven and physical models is developed in this paper as a grey box model for the exhaust emission prediction of a commercial vehicle diesel engine.

Within a project of the Research Association for Combustion Engines e.V., different measures for rising the temperature of exhaust gas aftertreatment components of both a passenger car and an industrial/commercial vehicle engine were investigated on a test bench as well as in simulation. With the passenger car diesel engine and different catalyst configurations, the potential of internal and external heating measures was evaluated. The configuration consisting of a NOx storage catalyst (NSC) and a diesel particulate filter (DPF) illustrates the potential of an electrically heated NSC. The exhaust aftertreatment system consisting of a diesel oxidation catalyst (DOC) and a DPF shows in simulation how variable valve timing in combination with electric heated DOC can be used to increase the exhaust gas temperature and thus fulfill the EU6 emission limits.

To understand how laminar burning velocities of standard unleaded gasoline-air-mixtures change by varying the concentration of oxygen in the combustible mixture, experimentally and numerical investigations are conducted in this work. Experiments were performed using a heatable pressure vessel which enables optical access. A monochromatic high-speed Schlieren cinematography measurement system combined with a high-speed CCD camera were used to track the propagating spherical flame fronts in the vessel. Numerically, freely propagating one dimensional laminar steady flame calculations were conducted for Primary-Reference-Fuel Air Mixtures (PRF87 or RON87), corresponding for standard gasoline combustible mixtures. Two combustible mixtures were investigated: (1) with air as oxidizer; (2) oxidizer consisting of 15% O2 and 85% N2 by mole fractions. The initial temperature for all investigated mixtures was 373 K.

In this work very rich premixed laminar spherical flame kernels of hydrocarbon-air combustible mixtures were experimentally and numerically investigated under microgravity conditions. These microgravity combustion experiments were carried out in the Drop Tower of Bremen University. The Closed-Vessel-Bomb-Method (CVBM) was applied for all experimental investigations combined with a monochromatic Helium-Neon-Schlieren Measurement Technique. Images of the propagating spherical flames were tracked with a High-Speed-Camera. The pressure vessel enables optical access and contains a volume of approx. half a litre. Combustible Mixtures were investigated at initial pressures up to 30 bar and initial temperatures were 420 K for all experiments, whereas the equivalence ratio for investigated N-Pentane-Air-Mixtures was Φ=3.0, N-Hexane-Air-Mixtures was Φ=3.3, N-Heptane-Air-Mixtures was Φ=3.5 and the equivalence ratio for investigated Isooctane-Air-Mixtures was Φ=3.9 for all experiments.

After the realization of very low exhaust gas emissions and corresponding OBD requirements to fulfill Euro VI and Tier 4 legislation, the focus in heavy-duty powertrain development is on the reduction of fuel consumption and thus CO₂ emissions again. Besides this, the total vehicle operation costs play another major role. A holistic view of the overall powertrain system including the combustion process, exhaust gas aftertreatment, energy recuperation and energy storage is necessary in order to obtain the best possible system for a given application. A management system coordinating the energy flow between the different subsystems while guaranteeing low exhaust emissions plays a major part in operating such complex architectures under optimal conditions.

The low-NOx standard for heavy-duty trucks proposed by the California Air Resources Board will require rapid warm-up of the aftertreatment system (ATS). Several different aftertreatment architectures and technologies, all based on selective catalytic reduction (SCR), are being considered to meet this need. One of these architectures, the close-coupled SCR (ccSCR), was evaluated in this study using two different physics-based, 1D models; the simulations focused on the first 300 seconds of the cold-start Federal Test Procedure (FTP). The first model, describing a real, EuroVI-compliant engine equipped with series turbochargers, was used to evaluate a ccSCR located either i) immediately downstream of the low-pressure turbine, ii) in between the two turbines, or iii) in a by-pass around the high pressure turbine.

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.

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.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

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.