Proton exchange membrane fuel cells are considered to be a promising technology for future low -emission aircraft. However, the actual performance of fuel cell systems under aviation conditions is still unclear. To address this knowledge gap, this work develops a detailed model of a fuel cell system for the propulsion of a regional aircraft. The interaction of the stacks and auxiliary components is studied with validated models for the fuel cell stack, humidifier, heat exchanger and compressor. These models are coupled with a novel sizing approach that finds the smallest feasible combination of components while optimizing the stack operating conditions for each flight phase. Based on this approach, a wide range of possible fuel cell system designs is compared in terms of their mass, efficiency, drag and volume. The results show that it is beneficial to optimize these performance criteria simultaneously in a pareto optimization problem. The aircraft ' s electrical power demand of 3.12 MW is provided by ten identical 312 kW fuel cell systems that are distributed along the wing. Based on the model, such a 312 kW fuel cell system is predicted to achieve an efficiency of 39 % during cruise and 49 % on ground, a specific power of 0.50 kW/kg, a power density of 0.39 kW/L and a cruise drag of 333 N. Compared to conventional aircraft engines, fuel cells have the drawback of an increased mass and drag. The achievable propulsion system efficiency with fuel cells is lower than that of large turbofan engines, but higher than that of turboprop engines for regional aircraft.

The Air-cooled and open cathode proton exchange fuel cell (PEMFC) offers particular advantages in terms of complexity and weight reduction. Therefore, it seems very attractive to support the aviation industry in their de-carbonisation process. Major challenges in terms of operational stability and reliability hinders this technology to be used in commercial applications. Therefore, this study thoroughly examines the conditioning and optimization of open cathode PEMFC stacks, drawing insights from experimental findings. Key areas of focus include the enduring impact of prehumidification, the quantification of efficiency enhancements through reconditioning via oxygen starvation, and the refinement of Electrochemical Impedance Spectroscopy (EIS) data analysis under non -stationary conditions. The pre -humidification enhances stack performance by improving cell voltages from 40.09 V to 41.37 V at 30 A, increasing membrane humidity and improving efficiency. Furthermore, the residual water in the stack also functions as evaporative cooling and can assist in limiting the operating temperature of the stack during system start up. However, it is demonstrated that excessive soaking with water leads to severe flooding phenomena at the beginning of operation. A reconditioning period of 100 s through oxygen starvation induces a notable increase in stack voltage, from 41.37 V to 47.79 V at 35 A, which decreases to 43.56 V after 10 min of operation. This corresponds to an average increase in electric energy provision of about 6.2% at constant hydrogen consumption, attributed to PtOx reduction and increased water production. Despite limitations outside the medium frequency range (approximately 10 Hz - 15 kHz) for non -stationary conditions, EIS aids in understanding of the stack behaviour and supports the interpretation of current and voltage results. A novel evaluation method enables the quantitative description of the condition using EIS data. This data reveals a considerable drop (on average about 21,5% for the 10 A point and about 27,4% for the 30 A point) in charge transfer resistances of the fuel cell from initial operation to measurements after overnight soaking and the first series of oxygen starvation recovery.

Hydrogen is one of the most promising power sources for meeting the aviation sector's long-term decarbonization goals. Although on-board hydrogen systems, namely, fuel cells, are extensively researched, the maintenance, repair and overhaul (MRO) perspective remains mostly unaddressed. This paper analyzes fuel cells from an MRO standpoint, based on a literature review and comparison with the automotive sector. It also examines how well the business models and key resources of MRO providers are currently suited to provide future MRO services. It is shown that fuel cells require extensive MRO activities and that these are needed to meet the aviation sector's requirements for price, safety and, especially, durability. To some extent, experience from the automotive sector can be built upon, particularly with respect to facility requirements and qualification of personnel. Yet, MRO providers' existing resources only partially allow them to provide these services. MRO providers' underlying business models must adapt to the implementation of fuel cells in the aviation sector. MRO providers and services should, therefore, be considered and act as enablers for the introduction of fuel cells in the aviation industry.

Proton exchange membrane fuel cells (PEMFCs) represent today one of the most common types of fuel cells for mobility applications due to their comparatively high-power density, low operating temperature, and low costs. A PEMFC regularly consists of a stack of individual cells in which each consists of polar plates and a membrane electrode assembly. To achieve the best possible electric conductivity over the series connection of cells, the contact pressure in between the cells must be uniformly distributed over the cell area. This pressure is usually applied to the stack by end plates, which frame the stack and are clamped together by bolts, which are tightened by a defined torque. Typically, these end plates are made from bulk material with no or limited optimization. Looking at mobility applications, e.g., in aerospace, a fuel cell should ideally provide high efficiency at the lowest weight. Based on this assumption, this paper uses topology optimization varying the material as well as the design space to derive new design concepts for the end plates of a PEMFC. The designs are compared with respect to an even stress distribution to the fuel cell stack, the weight of the plates, and the manufacturability in the laser powder bed fusion process. The most promising design is manufactured and results in a weight decrease of 48% compared to previously used aluminum bulk plates. Finally, the optimized base plates are applied to a test cell and the performance is compared to their conventional counterparts, showing a 1% increase in electric stack power despite the lower mass.

Durability of proton exchange membrane fuel cell systems under cold weather conditions is essential and a critical challenge for transportation applications. During cold storage the water remaining in the cells can freeze causing damage to the cell components. In order to avoid this degradation, fuel cells are commonly purged with dried gases during shutdown prior to its storage at subzero temperatures. This work investigates cold storage of PEMFC systems at temperatures down to -40°C with the aim of developing a shutdown procedure that leads to minimal degradation due to cold storage, while meets energy efficient and time requirements of aeronautical applications. To that end, several experiments were carried out with two different stacks (a 4 kW liquid cooled and a 100 W air cooled) under a wide range of operating parameters: cathode gas, purge temperature, anode and cathode gas purge flow rates, purge time and cold storage temperature. The fuel cell performance degradation due to ice formation was measured by the polarization curves conducted prior and after every F/T cycle. The effects of these operating parameters on the durability of the PEMFC systems under cold storage are evaluated. The obtained experimental results showed that very long purge process lead to further performance degradation at -10°C than shorter process at -40°C, which indicates that eliminating all remained water in the cells is not only inefficient, but also lead to degradation due to the drying process. Moreover, guidelines to improve shutdown procedure for cold storage of proton exchange membrane fuel cell systems for aeronautical applications are discussed.

This work investigates the integration of polymer electrolyte membrane fuel cells (PEMFC) into recently proposed hydrogen aircraft concepts. Based on a numerical optimization of the stack's operating conditions, the interrelated aspects of efficiency and system mass are explored. A novel 1D two-phase PEMFC stack model is developed that captures water management effects in detail and yet features sufficiently low computational cost to be used for system-level optimization. The stack model is validated for a wide range of temperatures, current densities and oxygen concentrations. In combination with auxiliary component models, it can relate the effects of the investigated parameters on cell-level water management to system-level effects. This allows for an improved understanding of the underlying design tradeoffs, particularly regarding pressurized operation and stack oversizing. The results show that the conditions that maximize the overall system efficiency for a given flight phase deviate significantly from those that merely maximize stack efficiency.

The startup ability and durability at winter conditions has been a key issue for fuel cell vehicles. To reduce ice formation and to improve the cold start and lifetime of the PEMFC system, the remained water is commonly purged with dry gases at shutdown. This paper proposes an alternative cold storage method based on the use of a methanol solution as antifreeze. In order to study the cold start ability of a PEMFC system by using this method, cold start experiments at -10°C were performed with a 4 kW PEMFC stack. The results show that the stack can be successfully started at -10°C after being stored with the methanol solution and after these cold starts no performance degradation was observed. Furthermore, the use of the antifreeze method at shutdown may reduce its time and improve the energy efficiency of the system.

The performance of a Polymer Electrolyte Fuel Cell (PEFC) system is influenced by the environmental conditions and its operational parameters. In particular, excess supply of oxygen must be ensured, to avoid inadmissible operating conditions as it determines the efficiency and operational stability of the system. When the PEFC-system is used for emergency power supply (e.g. aircraft safety system), the system reliability is crucial, because it emergency power supply is not a redundant application. The use of additional oxygen contributes to this topic (figure 1). It allows air independent operation. In addition, the cell voltage is increased by the higher oxygen partial pressure, which has a positive effect on efficiency and system performance. Due to the higher efficiency in oxygen operation, the required cooling capacity is reduced. Accordingly, a higher system performance can be achieved without adjusting the cooling system. The oxygen partial pressure can also be increased by the cathodic pressure using a pressure regulator valve. In oxygen operation a higher system performance is achieved by using pressurized oxygen from a tank without using additional electric energy. In air operation, a compressor and a regulator valve are used to increase the system pressure. As a drawback the performance increase is limited, because the electrical power demand of the compressor bounds the overall system performance. Additionally the intake air warms up and may have to be cooled. In an experimental study with a 4 kW PEFC-system the cathodic oxygen partial pressure is varied. It is shown that the system performance is positively affected by increasing the oxygen content compared to operation with a compressor at different pressures. The influence on the best possible operating temperature and the necessary cooling capacity are taken into account. Finally, arising prospects of this concept are discussed.

The startup ability of a polymer electrolyte fuel cell System from subzero temperatures is essential, especially for transportation applications in winter scenarios. Extensive research has been carried out on fuel cell cold start for automotive applications with cathode air supply. In this study oxygen enriched cathode gas is used during fuel cell cold start. The aim of this experimental work is to study the influence of the cathode gas oxygen content on the cold start behaviour of a PEFC stack. Numerous tests with a 4 kW commercial fuel cell system were conducted starting from -10 °C to lower temperatures like -20 °C varying the oxygen content and other operational parameters, like the oxygen excess ratio or the starting voltage of the fuel cell stack. It was found that increasing the oxygen content shortens the cold start duration. As it can be seen in the figure this improvement is nonlinear. Increasing the content of O2 up to 30-35% can significantly reduce the startup time. The cold start processes as well as the optimal parameter combination at very low temperatures for following cathode gas: pure oxygen, synthetic air (20.9% O2) and synthetic oxygen-enriched air (optimal % O2 for the system) are to be presented. Finally, some fuel cell system concepts to improve the fuel cell cold start capability including oxygen enrichment will be discussed.

A simulation model of a fuel cell system is created using a discretized image of the fuel cell membrane and the liquid cooled bipolar plate. Thus it is possible to link processes at cell level (overvoltage, diffusion processes in the membrane) with processes at cell stack level (coolant mass flow, exhaust gas recirculation). The simulation model achieves short computing times and thus enables sensitivity analyses to be performed efficiently for different operating parameters. Coupled heat and mass transfer processes take place in a liquid cooled low-temperature cell stack, while an electrical DC power is produced by the stack. The time-dependent equation systems of the mass and power balances for the fuel cell system are derived and discretized to determine the exact distribution of the waste heat in the outflowing media. As diffusion of water through the membrane is taken into account, the system behaviour of a low-temperature PEM cell stack is finely resolved that the effects of different system configurations and different operating strategies (gas temperature control, gas humidification, exhaust gas recirculation, variable environmental conditions, cold start) can be investigated with sufficient accuracy in a dynamic simulation. As the equation system of the mass balance includes the water diffusion term, the value of the membrane humidity is explicitly calculated as a function of time and coordinate. The modelling approaches are validated with the help of laboratory tests for a fuel cell cold start. A 4 kW fuel cell system with hydrogen and air or with hydrogen and oxygen will be used for validation. Simulation results for different cold start temperatures are presented and compared with the measured values (figure 1).

To ensure the required reliability and efficiency of a polymer electrolyte fuel cell (PEFC) system, an emergency situation in which the supply of ambient air has to be sealed off, is considered. In this case oxygen from a separate gas tank is fed to the fuel cell system. To prevent the loss of oxygen by the exhaust, the cathode gas can be fed back by cathode gas recirculation while oxygen is injected. Thereby the opportunity to feed back the humidity of the exhaust air for additional fuel cell humidification becomes available. The humidification of a PEFC is essential to ensure high protonic conductivity and reduce voltage losses. However, the water content of the inlet gas has to be regulated to prevent the electrodes from flooding. To control the humidity of the system the gas flow rate, the temperature of the fuel cell and the cathode gas can be adjusted. In addition, the enhanced water content in the system allows increasing the operating temperatures. This work focuses on an experimental study of a 12 kW PEFC‐system with cathode gas recirculation and a phenomenological model to optimize the fuel cell humidification depending on the operating parameters.

The German Federal Court of Justice (BGH) had to assess the outcome of price negotiations between a powerful German food retailer (Edeka) and some of its suppliers. Edeka had just taken over a…

Camera motion estimation from observed scene features is an important task in image processing to increase the accuracy of many methods, e.g., optical flow and structure-from-motion. Due to the curved geometry of the state space $${\text {SE}}_{3}$$SE3 and the nonlinear relation to the observed optical flow, many recent filtering approaches use a first-order approximation and assume a Gaussian a posteriori distribution or restrict the state to Euclidean geometry. The physical model is usually also limited to uniform motions. We propose a second-order optimal minimum energy filter that copes with the full geometry of $${\text {SE}}_{3}$$SE3 as well as with the nonlinear dependencies between the state space and observations., which results in a recursive description of the optimal state and the corresponding second-order operator. The derived filter enables reconstructing motions correctly for synthetic and real scenes, e.g., from the KITTI benchmark. Our experiments confirm that the derived minimum energy filter with higher-order state differential equation copes with higher-order kinematics and is also able to minimize model noise. We also show that the proposed filter is superior to state-of-the-art extended Kalman filters on Lie groups in the case of linear observations and that our method reaches the accuracy of modern visual odometry methods.

Camera motion estimation from observed scene features is an important task in image processing to increase the accuracy of many methods, e.g. optical flow and structure-from-motion. Due to the curved geometry of the state space SE(3) and the non-linear relation to the observed optical flow, many recent filtering approaches use a first-order approximation and assume a Gaussian a posteriori distribution or restrict the state to Euclidean geometry. The physical model is usually also limited to uniform motions. We propose a second-order minimum energy filter with a generalized kinematic model that copes with the full geometry of SE(3) as well as with the nonlinear dependencies between the state space and observations. The derived filter enables reconstructing motions correctly for synthetic and real scenes, e.g. from the KITTI benchmark. Our experiments confirm that the derived minimum energy filter with higher-order state differential equation copes with higher-order kinematics and is also able to minimize model noise. We also show that the proposed filter is superior to state-of-the-art extended Kalman filters on Lie groups in the case of linear observations and that our method reaches the accuracy of modern visual odometry methods.

We propose a variational approach for estimating egomotion and structure of a static scene from a pair of images recorded by a single moving camera. In our approach the scene structure is described by a set of 3D planar surfaces, which are linked to a SLIC superpixel decomposition of the image domain. The continuously parametrized planes are determined along with the extrinsic camera parameters by jointly minimizing a non-convex smooth objective function, that comprises a data term based on the pre-calculated optical flow between the input images and suitable priors on the scene variables. Our experiments demonstrate that our approach estimates egomotion and scene structure with a high quality, that reaches the accuracy of state-of-the-art stereo methods, but relies on a single sensor that is more cost-efficient for autonomous systems.

Accurate camera motion estimation is a fundamental building block for many Computer Vision algorithms. For improved robustness, temporal consistency of translational and rotational camera velocity is often assumed by propagating motion information forward using stochastic filters. Classical stochastic filters, however, use linear approximations for the non-linear observer model and for the non-linear structure of the underlying Lie Group SE_3 and have to approximate the unknown posteriori distribution. In this paper we employ a non-linear measurement model for the camera motion estimation problem that incorporates multiple observation equations. We solve the underlying filtering problem using a novel Minimum Energy Filter on SE_3 and give explicit expressions for the optimal state variables. Experiments on the challenging KITTI benchmark show that, although a simple motion model is only employed, our approach improves rotational velocity estimation and otherwise is on par with the state-of-the-art.

We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied both theoretical and numerical issues. While we were able to show the existence of solutions for a relatively broad class of problems, we encountered difficulties concerning uniqueness of the solution as well as convergence of existing algorithms for solving QVIs. In particular, it seemed that with increasing image size the growing condition number of the involved differential operator posed severe problems. In the present paper we prove uniqueness for a larger class of problems, particularly independent of the image size. Moreover, we provide a numerical algorithm with proved convergence. Experimental results support our theoretical findings.

We present an approach to jointly estimating camera motion and dense scene structure in terms of depth maps from monocular image sequences in driver-assistance scenarios. For two consecutive frames of a sequence taken with a single fast moving camera, the approach combines numerical estimation of egomotion on the Euclidean manifold of motion parameters with variational regularization of dense depth map estimation. Embedding this online joint estimator into a recursive framework achieves a pronounced spatio-temporal filtering effect and robustness. We report the evaluation of thousands of images taken from a car moving at speed up to 100 km/h. The results compare favorably with two alternative settings that require more input data: stereo based scene reconstruction and camera motion estimation in batch mode using multiple frames. The employed benchmark dataset is publicly available.