Dirk Uwe Sauer

Comparative study of a structured neural network and an extended Kalman filter for state of health determination of lithium-ion batteries in hybrid electricvehicles

State of health (SOH) determination becomes an increasingly important issue for a safe and reliable operation of lithium-ion batteries in hybrid electric vehicles (HEVs). Characteristic performance parameters as capacity and resistance change over lifetime and have to be determined precisely. This work deduces two different parameter estimation methods to identify the SOH of battery resistance and investigates the feasibility of an application in HEVs. First, a knowledge-based algorithm of a developed structured neural network (SNN). Thereby, the structure of the network is adopted from the mathematical description of the electrical equivalent circuit model. Two main advantages expected from a SNN compared to a regular neural network are: first a reduced structure and complexity of the network through predefined functions and thus faster computation, second the possibility to get access to internal parameters of the model. In order to verify a proper operation and performance of the developed SNN, a model-based second parameter estimation method is used with the well established the extended Kalman filter (EKF) algorithm. Furthermore, the developed algorithms are applied on real-vehicle data of a HEV battery at begin of life and after 170,000km. A verification of the identified states against reference data based on electro-chemical impedance spectroscopy shows nearby identical results for SNN and EKF. Additionally, a comparison of implementation effort and computation time isgiven.

A review of current automotive battery technology and future prospects

In this article, today’s battery technologies and future options are discussed. Batteries have been one of the main focuses of automotive development in the last years. Technologies that have been in use for a very long time, such as the lead–acid battery, are indispensable but need improvement. New technologies such as the lithium-ion battery are entering the market. Supercapacitors (also known as electrochemical double-layer capacitors) can be used for high-power requirements such as regenerative braking. The variety of vehicles has increased with the introduction of hybrid vehicles, plug-in hybrid vehicles and electric vehicles and, for each type, suitable battery types are being used or under development. Appropriate battery system designs and charging strategies are needed. Battery technologies can be classified according to their energy density, their charge and discharge characteristics, system integration and the costs. Further relevant performance parameters are the calendar lifetime, the cycle lifetime, the low- and high-temperature performances and the safety.

Selection and Performance-Degradation Modeling of LiMO

Advances in the development of energy storage technologies are making them attractive for grid integration together with wind power plants. Thus, the new system, the virtual power plant, is able to emulate the characteristics of todays conventional power plants. However, at present, energy storage devices are expensive and proper selection of the energy storage technology that is to be grid integrated with wind power plants is necessary. In this paper, a methodology for selection of the most suitable energy storage technology for grid integration with wind power plants is proposed. The selection process is service-oriented and thus the energy storage technology is selected based on certain requirement criteria. The primary frequency regulation service was chosen, for example, due to its potential economic benefits. For this service, low cost per cycle at partial charge/discharge was found as the requirement criterion while Li-ion batteries where found as the devices which could best fulfil this requirement. Since accurate and fast battery performance models are indispensable for studying the virtual power plant behavior under different operating conditions, impedance-based performance-degradation models were developed for the two most suitable Li-ion chemistries for the primary frequency regulation service: LiMO2/Li4Ti5O12 and LiFePO4/C.

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Current images of our future energy system include the assumption that a high proportion of renewable energies will be used. Relevant scenarios assume that by 2050 anywhere from 80 to even 100 percent of our electricity will be generated from renewable energy sources. In addition to power generating systems, the necessary ingredients for a working system with a high proportion of renewable energy sources include climate-friendly technologies for balancing the supply and demand of electricity. This is of particular importance with regard to wind turbines and photovoltaic systems whose supply often plummets due to adverse weather conditions. The Europaische Akademie has now published an interdisciplinary study entitled “Balancing Renewable Electricity. Energy Storage, Demand Side Management and Network Extension from an Interdisciplinary Perspective”. It provides a comprehensive overview of the use of energy storage systems, demand side management and extended networks for balancing supply and demand within systems which have a high proportion of renewable energy sources. Based on the results of a threeyear research project at the Europaische Akademie, researchers from the fields of power engineering, technology assessment, political science, economics and law are making recommendations in a joint effort for the development and implementation of climate-friendly strategies for balancing supply and demand within the electricity system. It will prove challenging to provide power according to different time scales – since it must be available within fractions of a second and continue to be available for several hours or days. Because of the challenge this task represents, the authors predict that a mixture of suitable technologies will eventually prevail. They have also come to the conclusion that significant development needs exist regarding energy storage, demand side management as well as electrical transmission and distribution networks. Promoting innovation in these areas requires, amongst others, a concept aimed at removing obstacles which arise from existing financial support of other energy technologies. So as to create a better basis for political measures, systems studies and scientific policy advisory work should also be expanded. Moreover, the authors perceive a need for amendments to be made in the legal field. Some important keywords in this context include: legal assignments of storage applications to the level of the generator or network, planning processes, how to deal with the large amounts of regularly generated sensitive data and the regulation of the manifold new business relationships which arise.

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Abstract In order to investigate the behaviour of valve-regulated lead/acid batteries in solar power applications, gel and AGM batteries were installed in different solar power systems. Each system is divided into several groups and each group has the same battery type, the same loading and the same solar generator. The only difference is the charge/discharge strategy. A key result after 2 years of testing is that the charge strategies which are typically used today in the field cannot charge the batteries completely. However, if the batteries were charged intensively afterwards they returned to full capacity. This means that there is a problem of undercharging in the field. Improving the charge/discharge strategy can, therefore, extend the service life and the energy turnover of VRLA batteries in solar power applications. Moreover, some existing VRLA battery types were modified with regard to the amount of electrolyte and phosphoric acid. These versions were investigated in the laboratory and are included in the field tests.

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As lithium-ion batteries play an important role for the electrification of mobility due to their high power and energy density, battery lifetime prediction is a fundamental aspect for successful market introduction. This work shows the development of a lifetime prediction model based on accelerated aging tests. To investigate the impact of different voltages and temperatures on capacity loss and resistance increase, calendar life tests were performed. Additionally, several cycle aging tests were performed using different cycle depths and mean SOC. Both the calendar and the cycle test data were analyzed to find mathematical equations that describe the aging dependence on the varied parameters. Using these functions an aging model coupled to an impedance-based electrical-thermal model was built. The lifetime prognosis model allows analyzing and optimizing different drive cycles and battery management strategies. The cells modeled in this work were thoroughly tested taking into account a wide range of influence factors. As validation tests on realistic driving profiles show, a robust foundation for simulation results is granted. Together with the option of using temperature profiles changing over the seasons, this tool is able to simulate battery aging in various applications.

Ti

Having discussed technical requirements, potentials and costs for balancing technologies in the previous sections, this chapter investigates problems in a market economy with electricity supply that changes with weather conditions and incentives to balance supply and demand (see Sect. 7.1). This is followed by an analysis of the reasons and potentials for politically manipulating economic framework conditions (see Sect. 7.2). The results are finally summarised and concluded in Sect. 7.3.

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Lithium-ion battery aging tests show that battery lifetime can be strongly influenced by the operating conditions, particularly by the state of charge and the cycle depth. Therefore a genetic optimization algorithm is applied to optimize the charging behavior of a plug-in hybrid electric vehicle (PHEV) connected to the grid with respect to maximizing energy trading profits in a vehicle-to-grid (V2G) context and minimizing battery aging costs at the same time. The simulation shows that the algorithm is able to increase the battery lifetime drastically and therefore reduces the mobility costs for the vehicle owner.

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The membrane is the key component of a redox flow system, as it has to avoid cross-contamination of the ions of the active material as well as to permit high proton conductivity. A membrane with drastically reduced cross-contamination ability would overcome the main problem of several redox couples and, in consequence, a wider variety of redox couples would potentially allow redox flow systems with higher energy densities or lower material costs. This work deals with modifications of Nafion membranes to decrease the cross-contamination ability without affecting the proton conductivity. Several in situ gel reactions were used for modification of the membranes. Cross-contamination has been reduced in this work by a factor of 2 compared to previous works by Xi et al. [J. Power Sources, 166, 531 (2007)] and Teng et al. [J. Power Sources, 189, 1240 (2009)].

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Combining a fuel cell (FC) as primary power source with a supercap (SC) as a buffer for high power demands is a promising approach for future hybrid electric vehicles (HEV). The objective of an energy management is to minimize the hydrogen consumption and to assure power availability at any time. A simulation environment incorporating models of the FC and SC stacks and the kinetic state of the vehicle allow the detailed analysis and comparison of control strategies. Control strategies that operate the fuel cell most efficiently and take best advantage of the supercap can save more than 20% hydrogen fuel.