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Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
Objective: This paper deals with the design and the optimization of mechatronic devices.
Introduction: Comparing with existing works, the design approach presented in this paper aims to integrate optimization in the design phase of complex mechatronic systems in order to increase the efficiency of this method.
Methods: To solve this problem, a novel mechatronic system design approach has been developed in order to take the multidisciplinary aspect and to consider optimization as a tool that can be used within the embodiment design process to build mechatronic solutions from a set of solution concepts designed with innovative or routine design methods.
Conclusions: This approach has then been applied to the design and optimization of a wind turbine system that can be implemented to autonomously supply a mountain cottage.
Process engineering focuses on the design, operation, control and optimization of chemical, physical and biological processes and has applications in many industries. Process Intensification is the key development approach in the modern process engineering. The proposed Advanced Innovation Design Approach (AIDA) combines the holistic innovation process with the systematic analytical and problem solving tools of the theory of inventive problem solving TRIZ. The present paper conceptualizes the AIDA application in the field of process engineering and especially in combination with the Process Intensification. It defines the AIDA innovation algorithm for process engineering and describes process mapping, problem ranking, and concept design techniques. The approach has been validated in several industrial case studies. The presented research work is a part of the European project “Intensified by Design® platform for the intensification of processes involving solids handling”.
Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
This paper describes the Sweaty II humanoid adult size robot trying to qualify for the RoboCup 2017 adult size humanoid competition. Sweaty came 2nd in RoboCup 2016 adult size league. The paper describes the main characteristics of Sweaty that made this success possible, and improvements that have been made or are planned to be implemented for RoboCup 2017.
Technology and computer applications influence our daily lives and questions arise concerning the role of artificial intelligence and decision-making algorithms. There are warning voices, that computers can, in theory, emulate human intelligence-and exceed it. This paper points out that a replacement of humans by computers is unlikely, because human thinking is characterized by cognitive heuristics and emotions, which cannot simply be implemented in machines operating with algorithms, procedural data processing or artificial neural networks. However, we are going to share our responsibilities with superior computer systems, which are tracking and surveying all of our digital activities, whereas we have no idea of the decision-making processes inside the machines. It is shown that we need a new digital humanism defining rules of computer responsibilities to avoid digital totalism and comprehensive monitoring and controlling of individuals within the planet Earth.
Automatic Identification of Travel Locations in Rare Books - Object Oriented Information Management
(2017)
The digital content of the Internet is growing exponentially and mass digitization of printed media opens access to literature, in particular the genre of travel literature from the 18th and 19th century, which consists of diaries or travel books describing routes, observations or inspirations. The identification of described locations in the digital text is a long-standing challenge which requires information technology to supply dynamic links to sources by new forms of interaction and synthesis between humanistic texts and scientific observations.
Using object oriented information technology, a prototype of a software tool is developed which makes it possible to automatically identify geographic locations and travel routes mentioned in rare books. The information objects contain properties such as names and classification codes for populated places, streams, mountains and regions. Together, with the latitudes and longitudes of every single location, it is possible to geo-reference this information in order that all processed and filtered datasets can be displayed by a map application. This method has already been used in the Humboldt Digital Library to present Alexander von Humboldt’s maps and was tested in a case study to prove the correctness and reliability of the automatic identification of locations based on the work of Alexander von Humboldt and Johann Wolfgang von Goethe.
The results reveal numerous errors due to misspellings, change of location names, equality of terms and location names. But on the other hand it becomes very clear that results of the automatic object detection and recognition can be improved by error-free and comprehensive sources. As a result an increase in quality and usability of the service can be expected, accompanied by more options to detect unknown locations in the descriptions of rare books.
Micro gas turbines (MGTs) are regarded as combined heat and power (CHP) units which offer high fuel utilization and low emissions. They are applied in decentralized energy neration.
To facilitate the planning process of energy systems, namely in the context of the increasing application of optimization techniques, there is a need for easy-to-parametrize component models with sufficient accuracy which allow a fast computation. In this paper, a model is proposed where the non-linear part load characteristics of the MGT are linearized by means of physical insight of the working principles of turbomachinery. Further, it is shown that the model can be parametrized by the data usually available in spec sheets. With this model a uniform description of MGTs from several manufacturers
covering an electrical power range from 30kW to 333kW can be obtained. The MGT model was
implemented by means of Modelica/Dymola. The resulting MGT system model, comprising further heat exchangers and hydraulic components, was validated using the experimental data of a 65kW MGT from a trigeneration energy system.
Polygeneration systems are a key technology for the reduction of primary energy usage and emissions. High costs, lack of flexibility and effort for parameterization hinder the wide usage of modeling tools during their conceptual design. This paper describes how planning tools can be structured for the conceptual design phase where only little information is available to the planner. A library concept was developed using the principles of object-oriented modeling to address the flexibility issue. With respect to cost and expandability, the open-source modeling language Modelica was chosen. Furthermore, easy-to-parameterize component models were developed. In addition to the improved library concept and novel component models, an easy-to-adapt control concept is proposed. The component models were validated and the applicability of the library was demonstrated by means of an example. It was shown that the data usually obtained from spec sheets are sufficient to parameterize the models. In addition to this, the control concept was approved.
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products (e.g., fuel cells, metal/air cells, electrolyzers) offer an additional observable, that is, the gas pressure. The dynamic coupling of current and/or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. This sensitivity can be exploited for model parameterization and validation. A general analysis of EPIS is presented, which shows the necessity of model-based interpretation of the complex EPIS shapes in the Nyquist plot (cf. Figure). We then present EPIS simulations for two different electrochemical cells: (1) a sodium/oxygen battery cell and (2) a hydrogen/air fuel cell. We use 1D or 2D electrochemical and transport models to simulate current excitation/pressure detection or pressure excitation/voltage detection. The results are compared to first EPIS experimental data available in literature [2,3].
A complete thermomechanical fatigue (TMF) life prediction methodology is developed for predicting the TMF life of cast iron cylinder heads for efficient heavy duty internal combustion engines. The methodology uses transient temperature fields as thermal loads for the non-linear structural finite-element analysis (FEA). To obtain reliable stress and strain histories in the FEA for cast iron materials, a time and temperature dependent plasticity model which accounts for viscous effects, non-linear kinematic hardening and tensioncompression asymmetry is required. For this purpose a unified elasto-viscoplastic Chaboche model coupled with damage is developed and implemented as a user material model (USERMAT) in the general purpose FEA program ANSYS. In addition, the mechanismbased DTMF model for TMF life prediction developed in Part I of the paper is extended to three-dimensional stress states under transient non-proportional loading conditions. The material properties of the plasticity model are determined for lamellar graphite cast iron GJL250 and vermicular graphite cast iron GJV450 from isothermal and non-isothermal uniaxial tests. The methodology is applied to obtain a TMF life prediction on two cast iron cylinder heads for heavy duty diesel engine applications made from both cast iron materials. It is shown that the life predictions using the developed methodology correlate very well with observed lives from two bench tests in terms of location as well as number of cycles to failure.
The DMFC is a promising option for backup power systems and for the power supply of portable devices. However, from the modeling point of view liquid-feed DMFC are challenging systems due to the complex electrochemistry, the inherent two-phase transport and the effect of methanol crossover. In this paper we present a physical 1D cell model to describe the relevant processes for DMFC performance ranging from electrochemistry on the surface of the catalyst up to transport on the cell level. A two-phase flow model is implemented describing the transport in gas diffusion layer and catalyst layer at the anode side. Electrochemistry is described by elementary steps for the reactions occurring at anode and cathode, including adsorbed intermediate species on the platinum and ruthenium surfaces. Furthermore, a detailed membrane model including methanol crossover is employed. The model is validated using polarization curves, methanol crossover measurements and impedance spectra. It permits to analyze both steady-state and transient behavior with a high level of predictive capabilities. Steady-state simulations are used to investigate the open circuit voltage as well as the overpotentials of anode, cathode and electrolyte. Finally, the transient behavior after current interruption is studied in detail.
Passive hybridization of battery cell and photovoltaic cell: modeling and experimental validation
(2017)
Lithium-ion batteries show a complex thermo-electrochemical performance and aging behavior. This paper presents a modeling and simulation framework that is able to describe both multi-scale heat and mass transport and complex electrochemical reaction mechanisms. The transport model is based on a 1D + 1D + 1D (pseudo-3D or P3D) multi-scale approach for intra-particle lithium diffusion, electrode-pair mass and charge transport, and cell-level heat transport, coupled via boundary conditions and homogenization approaches. The electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA, allowing flexible multi-phase electrochemistry to describe both main and side reactions such as SEI formation. A model of gas-phase pressure buildup inside the cell upon aging is added. We parameterize the model to reflect the performance and aging behavior of a lithium iron phosphate (LiFePO4, LFP)/graphite (LiC6) 26650 battery cell. Performance (0.1–10 C discharge/charge at 25, 40 and 60°C) and calendaric aging experimental data (500 days at 30°C and 45°C and different SOC) from literature can be successfully reproduced. The predicted internal cell states (concentrations, potential, temperature, pressure, internal resistances) are shown and discussed. The model is able to capture the nonlinear feedback between performance, aging, and temperature.