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Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

The advent of digitalization opens up new avenues for advances in large internal combustion engine technology. Key engine components are becoming "intelligent" through advanced instrumentation and data analytics. By generating value-added data, they provide deeper insight into processes related to the components. An intelligent common rail diesel fuel injection valve for large engine applications in combination with machine learning allows reliable prediction of key combustion parameters such as maximum cylinder pressure, combustion phasing and indicated mean effective pressure. However, fault-related changes to the injection valve also have to be considered. Based on experiments on a medium-speed four-stroke single-cylinder research engine with a displacement of approximately 15.7 liter, this study investigates the extent to which the intelligent injection valve can improve the reliability of combustion parameter predictions in the presence of injection valve faults.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.

Modeling of lithium iron phosphate electrodes calls for appropriate extensions of established model approaches. An electrochemical pseudo two-dimensional and a single-particle model are enhanced to address the phase separating behavior of this material with a variable solid state diffusion model. A particle size distribution model tackles the heterogeneity of the electrode microstructure. Both models are embedded in a framework to describe multi-layer electrode designs featuring segregated material properties. The models are parameterized following literature replicating a good match with measured discharge curves at low, medium and high currents. A simplified version of the rigorous model shows the effort of reparameterization, the computational advantage of model order reduction techniques, the model accuracy and application scope.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining modular component technology with integration and industrialization requirements when heading for further significant efficiency optimization. At the same time focus on reduced development time, product cost and minimized additional investment demand reuse of current production, machining, and assembly facilities as far as possible. Up to date additive manufacturing (AM) is an established prototype component, as well as tooling technology in the powertrain development process, accelerating procurement time and cost, as well as allowing to validate a significantly increased number of variants. The production applications of optimized, dedicated AM-based component design however are still limited.

Hydrogen promises to provide some highly desired features for clean and efficient combustion, but harvesting efficiency and emission potentials as well as meeting engine durability requirements needs careful adaption of both, combustion system components and engine operation strategies. Key points for H2-ICE combustion are some specific and unique features of H2/air mixtures, among which – to name only a few – excellent dilutability, lean burn capability, low ignition energy and high molecular diffusivity and their consequences on ICE operation do play prominent roles. H2 admission via port or direct injection, compression ratio selection and injection timing provide a set of parameters to control combustion features.

Within gear pair development, the simulation of loaded transmission error, line of action and summarized mesh point are crucial information in design optimization as well as reliability, NVH and efficiency prediction. These properties and variables are difficult to evaluate and are usually only assessed through proxy-variables such as unloaded transmission error or contact pattern assessment. Alternatively, large design loops can be generated when prototypes are produced to directly assess the results of reliability, NVH and efficiency and simulation models updated to the results, but not directly calibrated. This work will showcase an advanced test facility with the unique capabilities to evaluate all gear contact types (including hypoid, beveloid, cylindrical and spiral) under loaded conditions while assessing position and force data that can be used to validate simulation models directly and enhance design development.

This work elaborates the transferability of electrode diffusion coefficients gained from fitting procedures in frequency domain to an electrochemical battery model run in time domain. An electrochemical battery model of an NMC622 half-cell electrode is simulated with sinusoidal current excitations at different frequencies. The current and voltage signals are analyzed in frequency domain via Nyquist and Bode plots. The frequency domain analysis of time domain simulations is applied to assess the numerical convergence of the simulation and the sensitivity on particle diameter, electrode and electrolyte diffusion coefficients. The simulated frequency spectra are used to fit the electrode diffusion coefficient by means of different electrical equivalent circuit models and the electrochemical battery model itself. The fitted diffusion coefficients from the different electrical equivalent circuit models deviate by one order of magnitude from the a priori known reference data.

Increasingly stringent greenhouse gas and emission limits demand for powertrain electrification throughout all vehicle applications. Beside fully electric powertrains different configurations of hybrid powertrains will have an important role in upcoming and future vehicle generations. As already discussed in previous papers, the requirements on the combustion engine in hybrid powertrains are different to those in a conventional powertrain solution, heading for brake thermal efficiency targets of 45% and above within the product lifecycle for conventional fuels. Focus on product cost and production and assembly facility investment drives reuse of technology packages within modular powertrain technology platforms, with different combinations of internal combustion engines (ICE), transmissions, and e-drive-layouts. The goal of zero carbon operation requires compatibility of ICE for sustainable fuels.

As electrified powertrains trends towards the new norm in development, the need to consider modular development approaches becomes more prevalent. Modular system developments seek to offer an adaptable product range by considering each system component (transmission, e-motor, inverter, battery, etc.) and system element (park-lock, disconnect, differential, etc.) as interchangeable. This can result in a lower cost development process overall to increase the returns for tier1 suppliers by expanding the marketability of the platform. Such an approach has hitherto held relatively low commercial interest as the rate of technological advancement negated the benefits of a modular development due to the lack of long-term competitivity. Previously large technological advances between successive productions and the relatively limited EV market, centred around SUV and small car applications, reduced the value in committing to a platform development.

Fully flexible dual fuel (DF) internal combustion (IC) engines, that can burn diesel and gas simultaneously, have become established among heavy-duty engines as they contribute significantly to lower the environmental impact of the transport sector. In order to gain better understanding of the DF combustion process and establish an effective design methodology for DFIC engines, high fidelity computational fluid dynamics (CFD) simulation tools are needed. The DF strategy poses new challenges for numerical modelling of the combustion process since all combustion regimes have to be modelled simultaneously. Furthermore, DF engines exhibit higher cycle-to-cycle variations (CCV) compared to the pure diesel engines. This issue can be addressed by employing large eddy simulation coupled with appropriate DF detailed chemistry mechanism. However, such an approach is computationally too expensive for today’s industry-related engine calculations.

System lubrication in automotive powertrains is a growing topic for development engineers. Hybrid and pure combustion system complexity increases in search of improved efficiency and better control strategy, increasing the number of components with lubrication demand and the interplay between them, while fully electric systems drive for higher input speeds to increase e-motor efficiency, increasing bearing and gear feed rate demands. Added to this, many e-axle and hybrid systems are in development with a shared medium and circuit for e-motor cooling and transmission lubrication. Through all this, the lubricant forms a common thread and is a fundamental component in the system, but no standardized tests can provide a suitable methodology to investigate the adequate lubrication of components at powertrain level, to support the final planned vehicle usage.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining component technology with integration and industrialization requirements when heading for further significant efficiency optimization of the subsystem internal combustion engine. The requirements on the combustion engine in hybrid powertrains are quite different to those in a conventional powertrain solution. Next-generation hybrid engines, with brake thermal efficiency (BTE) targets starting from 42-43% and aiming for 45% and above within the product lifecycle, require a re-thinking of the base engine architecture of current modular engine platforms. At the same time focus on the product cost and minimized additional investment demand reuse of current production, machining and assembly facilities as far as possible.

Fast charging of batteries at cold conditions faces the challenge of promoting undesired cell degradation phenomena such as lithium plating. The occurrence of lithium plating is strongly related to local surface potentials and temperatures involving the scales of the electrode surface, the unit cell and the entire module or pack. A multi-scale, multi-domain model is presented, enhancing a Newman based unit cell model with consistent models for heat generation and lithium plating and integrating this 1D+1D approach into a thermal 3D model on module level. The basic equations are presented and three different plating models from literature are discussed. The thermal model is assessed in open-loop simulations and the different plating approaches are compared in charge/discharge simulations at different operating conditions. The full multi-scale, multi-domain model is applied as a virtual sensor for model-based control of fast charging at cold conditions.

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

The advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

The trend towards renewable energy sources will continue under the pre-amble of greenhouse gas (GHG) emission reduction targets. The main question is how to harvest and store renewable energy properly. The challenge of intermittency of the renewable energy resources make the supply less predictable compared to the traditional energy sources. Chemical energy carriers like hydrogen and synthetic fuels (e-Fuels) seem to be at least a part of the solution for storing renewable energy. The usage of e-Fuels in the existing ICE-powered vehicle fleet has a big lever arm to reduce the GHG emissions of the transport sector in the short- and medium term. The paper covers the whole well-to-wheel (WtW) pathway by discussing the e-Fuel production from renewable sources, the storage and the usage in the vehicle. It will be summarized by scenarios on the impact of e-Fuel to the WtW CO2 fleet emissions.

Spark Ignited (SI) combustions engines in combination with different degrees of hybridization are expected to play a major role in future vehicle propulsion. Due to the combustion principle and the related thermodynamic efficiency, it is especially challenging to meet future CO2 targets. The layout and optimization of the overall system requires novel methods in the development process which feature a seamless transition between real and virtual prototypes. Herein, engine models need to predict the entire engine operating range in steady-state and transient conditions and must respond to all relevant control inputs. In addition, the model must feature true real-time capability. This work presents a holistic and modular modeling framework, which considers all relevant processes in the complex chain of physical effects in SI combustion.