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Abstract. With the COP28 decisions the world is thriving for a future net-zero-CO2 society and the and current regulation acts, the energy infrastructure is changing in direction of renewables in energy production. All industry sectors will extend their share of direct or indirect electrification. The question might arise if the build-up of the renewables in energy production is fast enough. Demand and supply might not match in the short- and mid-term. The paper will discuss the roadmaps, directions and legislative boundary parameter in the regenerative energy landscape and their regional differences. National funding on renewables will gain an increasing importance to accelerate the energy transformation. The are often competing in attracting the same know-how on a global scale. In addition the paper includes details about energy conversion, efficiency as well as potential transport scenarios from production to the end consumer.

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.

Traditionally, Electric Machine design has primarily focused on factors like efficiency, packaging, and cost, often neglecting the critical aspects of Noise, Vibration, and Harshness (NVH) in the early decision-making stages. This disconnect between E-Machine design teams and NVH teams has consistently posed a challenge. This paper introduces an innovative workflow that unifies these previously separate domains, facilitating comprehensive optimization by seamlessly integrating NVH considerations with other E-Machine objectives, such as electromagnetic compatibility (EMC). This paper highlights AVL's approach in achieving this transformation and demonstrates how this integrated approach sets a new standard for E-Machine design. The presented approach relies on AI-driven algorithms and computational tools.

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.

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.

Validation of powertrain systems is nowadays performed with specific durability relevant load cycles, which represent the lifetime requirement of individual powertrain components. The definition of such durability relevant load cycles, which are used for vehicle testing should ideally be based on the actual vehicle's usage. Recording driving cycles within a vehicle is one of the most typical ways of collecting vehicle usage and relevant end customer behavior, but the generation of such measured vehicle data can be time consuming. In addition, this method of capturing on-road measurements has limitations in the variation of vehicle loadings (e.g., number of passengers, luggage, trailer usage etc.). Especially for new applications, entering new target markets, these kinds of in-vehicle measurements are not possible in early development stages, as the required vehicle or powertrain configuration is not available in hardware or incapable of measurements.

India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.

Vibration testing is common in automotive industry validation and gains greater significance with increasing numbers of electrical components, which are particularly suspectable to vibration related failures. While the nature and intention of vibration testing is common, many contradicting testing standards claim to be a one-size-fits-all solution, leading to questions of which standard is correct for any specific application. This is compounded by the vast variation in vehicle types and applications (suspension systems, dampers, powertrain mass, tire radius, intended usage, etc.) This paper seeks to offer and demonstrate a method to determine characteristic vibration profiles, based on vehicle classes, and illuminate the process to accelerate these to an appropriate test profile. This can either be used to directly validate a system or to support the selection of the most appropriate vibration profile from options within standards.

1 Autonomous Driving Systems (ADS) are developing rapidly. As vehicle technology advances to SAE level 3 and above (L4, L5), there is a need to maximize and verify safety and operational benefits. As a result, maintenance of these ADS systems is essential which includes scheduled, condition-based, risk-based, and predictive maintenance. A lot of techniques and methods have been developed and are being used in the maintenance of conventional vehicles as well as other industries, but ADS is new technology and several of these maintenance types are still being developed as well as adapted for ADS. In this work, we are presenting a systematic literature review of the “State of the Art” knowledge for the maintenance of a fleet of ADS which includes fault diagnostics, prognostics, predictive maintenance, and preventive maintenance.

The National Highway Traffic Safety Administration (NHTSA) has developed the Large Omnidirectional Child (LODC) Anthropomorphic Test Device (ATD) to improve the biofidelity of the currently available Hybrid III 10-year-old (HIII-10C) ATD. The improvements of the LODC over the HIII-10C include changes in sub-assemblies such as the head and neck, where the LODC head is a redesigned HIII-10C head with pediatric mass properties and the neck has a modified atlanto-occipital joint to replicate observations made from human specimens. The current study focuses on developing a dynamic, nonlinear finite element (FE) model of the LODC ATD head and neck complex. The FE mesh is generated using HyperMesh based on the three-dimensional CAD model. The material data, contact definitions and initial conditions are defined in LS-PrePost and converted to LS-Dyna solver input format. The initial and boundary conditions are defined to replicate the neck flexion experimental tests.

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.

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the finite volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1]. In that work, it was shown that the same accuracy of predicted aerodynamic forces can be achieved by using Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model on both types of meshes, the standard body-fitted (BF), and on the immersed boundary (IB) mesh. Due to all well-known shortcomings of the steady state approach, in this work we deal with the Partially Averaged Navier-Stokes (PANS), which belongs to the hybrid RANS-LES (scale resolving / high fidelity) methods. This approach was developed to resolve a part of the turbulence spectrum adjusting seamlessly from RANS to DNS (Direct Numerical Simulation).

This research leverages publicly available crash data to construct safety-critical scenarios focusing primarily on Level 3 Automated Driving Systems (ADS) safety assessment under highway driving conditions. NHTSA’s Crashworthiness Data System (CDS) has a rich dataset of representative crashes sampled from numerous Primary Sampling Units (PSUs) across the country. Each of these datasets includes the storyline, road geometry information, detailed description of actors involved in the crash, weather information, scene diagrams, crash images, and a myriad of other crash-specific details. The methodology adopted aims to generate critical scenarios from real-world driving to complement the existent regulatory tests for the validation of L3 ADS. For this work, a four-step approach was adopted to extract safety-critical scenarios from crash data.

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.

In recent years, many motorsports have been developing competitions based on electric vehicles. The demanding performance requires the battery pack to have the perfect balance between energy, power, and weight. This research paper presents a systematic methodology for the initial design of the battery pack (size and cell chemistry) by statistically analyzing the characteristics of the mission profile. The power profile for the battery pack of a motorsport vehicle can be estimated by considering the duty cycle of a racing car using the technical and sporting regulations and vehicle parameters. In this paper, many statistical metrics correlated to this power profile have been defined and analyzed (such as the max, mean, and standard deviation of the power profile, the total energy consumed, and the expected heat generation). These metrics have been used to estimate the cell energy and power density requirement and the pack sizing considering the weight constraints.

This paper presents calculations of external car aerodynamics by using the finite volume (FV) immersed-boundary method. The FV numerical codes primarily employ Reynolds-Averaged Navier-Stokes (RANS) models. In recent years, and due to possibility to run very large computational meshes, these models are usually used in conjunction with the advanced near-wall models. Moreover, it has been often demonstrated that the accuracy of RANS near-wall models relies on the mesh quality near the wall so by the rule, larger number of wall body-fitted cell-layers are employed. An immersed boundary (IB) method becomes an attractive alternative to the ‘standard’ FV approaches especially when applied to low quality CAD data. In general, the IB method is less investigated and validated for the car aerodynamics, particularly in conjunction with advanced near-wall turbulence models and an adaptive mesh refinement (AMR).

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.

In the last decade, the use of Driver-in-the-Loop (DiL) simulators has significantly increased in research, product development, and motorsports. To be used as a verification tool in research, simulators must show a level of correlation with real-world driving for the chosen use case. This study aims to assess the validity of a low-cost, limited travel Vehicle Dynamics Driver-in-Loop (VDDiL) simulator by comparing on-road and simulated driving data using a statistical evaluation of longitudinal and lateral metrics. The process determines if the simulator is appropriate for verifying control strategies and optimization algorithms for longitudinal vehicle dynamics and evaluates consistency in the chosen metrics. A validation process explaining the experiments, choice of metrics, and analysis tools used to perform a validation study from the perspective of the longitudinal vehicle model is shown in this study.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Still, major challenges for large scale deployment remain. They include higher maturity with respect to performance (e.g., range, interaction with the grid), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. New opportunities arise to customize road transportation systems toward application-driven, user-centric smart mobility solutions.

To improve the biofidelity of the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD), the National Highway Traffic Safety Administration (NHTSA) has developed the Large Omnidirectional Child (LODC) ATD. The LODC head is a redesigned HIII-10C head with mass properties and modified skin material required to match pediatric biomechanical impact response targets from the literature. A dynamic, nonlinear finite element (FE) model of the LODC head has been developed using the mesh generating tool Hypermesh based on the three-dimensional CAD model. The material data, contact definitions, and initial conditions are defined in LS-PrePost and converted to LS-Dyna solver input format. The aluminum head skull is stiff relative to head flesh material and was thus modeled as a rigid material. For the actual LODC, the head flesh is form fit onto the skull and held in place through contact friction.