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The importance of batteries is increasing, especially in the field of the high power requirement systems like electric driven vehicles. Mobile energy storage makes it possible to accelerate with incredible torque, without any accruing air pollution. Due to the high costs of real components, it is of great use to simulate battery driven systems before building them. Transient processes within a cell are highly dependent on the operating point of the complete system, which makes it difficult to create equations and model arameterizations. This paper shows which data is important for cell modeling and how to parameterize simplified physical cell models.
In this paper a design method for mechatronic functions in an early design phase under consideration of the requirements of functional safety is proposed [14]. The goal of the method is to discover threats for the safety goals and to prove or optimize the diagnostic mechanisms. At the current design process a lifetime endurance test is performed in a late project phase. In order to avoid unexpected late design changes the method should be applied in an early design phase. The method is an additional way to avoid design failures for E/E functions with special focus on aging in the field of functional safety applications. The method is developed out of three standards VDI 2221 methodology for development and construction of technical systems and products [1]), VDI 2206 design methodology for mechatronic systems [2] and the ISO 26262 road vehicles - Functional Safety [3] by using the V-Model. Furthermore, a core element of the design method is simulating aging effects by applying VHDL - AMS. To demonstrate the design methodology a sensor out of the EGAS function is chosen as a safety relevant automotive system. The limitation is the availability of aging data for electrical components.
For the planning of photovoltaic power plants standard software tools are used. Most of these software tools use statistical solar data to determine the overall energy harvest of a photovoltaic plant over one year. The calculations rely on stationary location and ideal boundary conditions, e.g., constant ambient temperature. Even though, for example, shadowing may be considered by standard software, the investigation of untypical configurations and problems cannot be performed by such software, as most configurations cannot be changed by the user.
The presented PhotoVoltaics library was developed with the intention to provide a flexible framework for standard and non-standard problems. Particularly, the PhotoVoltaics library can be coupled with other Modelica libraries to perform systemic investigations. An application library, PhotoVoltaics_TGM, is provided as add-on, where measured data of two photovoltaic pants of the TGM in Vienna can be compared with simulation results. This add-on library serves as validation of the PhotoVoltaics library.
Conventional battery management systems typically adopt hierarchical master-slave architectures. With regard to an uninterruptible power supply, the most significant disadvantage of central structures is the dependency of the errorfree function of the superior master board. The decentralized battery management system presented in this paper, consisting of consumers, generators and intelligent battery cells, is controlled without any central coordination authority. For this purpose, an intelligent control algorithm and a leader election algorithm are implemented on the microcontrollers of the battery cells. To test different control and election strategies, a software framework is presented for the complete simulation of the decentralized battery management system consisting of equal participants.
The automotive industry is eventually evolving into a complex network of services. The heterogeneous and distributed nature of automotive software systems demands flexible software components which can operate in different environments. Because of heterogeneous automotive development environments, the domain experts, must cope with too many diversities, adaption layers, and incompatibilities to design applications for the current generation of autonomous driving vehicles. In this context, interface adaptation is a promising approach to achieve flexibility without directly changing the respective components. AUTOSAR, which is the de-facto standard for describing automotive system architecture and is a hugely comprehensive standard allowing designers full control from abstract system description to bare metal level deployment. However, the vehicle subsystems have still evolved to include multifarious high-level domains not covered by AUTOSAR e.g. Infotainment, Telematics etc. Therefore, it seems beneficial to bridge the semantic gaps between AUTOSAR applications and other standards of automotive application domains. The goal of this paper is to investigate interface semantic mapping and achieve transparent integration of domain-specific applications using the translation of semantics among the AUTOSAR platform software component models and other software components models of open source development platforms e.g. GENIVI. A key goal of such a modelling approach is the reuse of existing interface description languages and respective code generators. This will enhance future interoperability and decrease in incompatibility among these platforms.
A magnetoelectric (ME) voltage transformer is fabricated on the basis of a ferromagnetic (FM)-piezoelectric (PE) heterostructure comprising two equally thick laminated layers of an amorphous FM alloy and a piezoceramic lead zirconate-titanate layer sandwiched between them. The structure, placed inside an excitation coil, is electrically poled and magnetized in the direction of the long axis. The primary voltage is applied to the coil and the secondary voltage is measured between the electrodes of the PE material. It is shown for the first time that the change in the total thickness of magnetic layers significantly influences the transformer ' s characteristics. At the largest total thickness of FM layers of 138 mu m, the open-circuit voltage transformation ratio K has a maximum value of about 20, and the power transfer efficiency eta at a matched resistive load of about 20 k omega reaches 45%. The variation of the control magnetic field in the range of 0-21.6 kA m(-1) makes it possible to change the voltage transformation ratio K from zero to the maximum value. A simple model allows one to calculate the dependence of the characteristics of the ME transformer on the frequency of the primary voltage, thickness of the FM layers, control magnetic field, and the load.
How is energy storage integrated and currently implemented in the electricity supply, heating supply, and mobility sectors? This chapter provides both theoretical and practical answers to that question. The chapter focuses on the integration of renewable energy. Cross-sectoral energy storage systems that link the electricity, heating, and mobility sectors are discussed in Kap. 14. This chapter focuses on storage integration in the electricity sector. After considering stand-alone networks, the chapter uses practical examples to analyze the various storage applications in the European network. The chapter concludes with a discussion of storage integration in the heating and transportation sectors.
Energy supply always requires energy storage—either as an intrinsic property or as additional system. It is an intrinsic property of solid, liquid, and gaseous fuels, although less so of water-borne heat, but not of electricity. So to meet variable demands and supplies, heat and electricity networks usually require additional storage systems. When they are added to an energy network, should they be viewed as ‘suppliers’ or as ‘consumers’? Who is responsible for covering the costs of storage systems? To categorize storage systems in the energy sector, they first need to be carefully defined.
This chapter defines storage as well as storage systems, describes their use, and then classifies storage systems according to temporal, spatial, physical, energy-related, and economic criteria.
Electricity is becoming the primary source of energy, a trend that is particularly apparent through the coupling of the electricity sector with other energy sectors. In addition to the established links between the electricity and heating sectors using combined heat and power (CHP), which is supplemented by electric heat-pumps and power-to-heat (PtH), other new links are also emerging. These links are manifesting in the form of electro-mobility and electric fuels in the electricity and transport sectors; and in the electricity and gas sector they are appearing in the form of power-to-gas (PtG). The production of basic chemical materials such as methanol or polymers using electrical energy, water, and CO2 will also play a role in the future. However, the latter will not be dealt with explicitly here. Instead we will consider in detail other aspects of electricity as a primary energy source and its integration and application for energy storage.
Human beings have relied on stored energy since time immemorial. The planet’s first mechanism for storing energy arose two billion years ago. Photosynthesis captures solar energy in chemical bonds; it is a process on which all life depends. With the discovery of fire around one-and-a-half million years ago, early man learned to access this stored energy by burning wood. Only since the Industrial Revolution have humans used fossil fuels, which are the results of biomass produced millions of years ago, then subjected to geological processes. Today, the long-term objective is to utilize sustainable biomass storage, replicate it by technical means, and to develop new storage technologies.
This chapter is about the history of energy storage as it pertains to the carbon cycle. It begins with a natural energy storage system—photosynthesis—and examines its products biomass, peat, and fossil fuels before turning to storage technology in the era of renewable energies. It will also discuss how stored energy is used. This chapter focuses on natural biogenic and fossil energy storage. Other chapters are devoted to artificial storage technologies, including batteries, pumped-storage, and power-to-gas (PtG). Each begins with a short history of its respective technology.