A ripple reduction method for a two stages battery charger with multi-winding transformer using notch filter

This paper presents a two-stage battery charger consisting of a bridgeless Totem-pole power factor correction (TP-PFC) circuit and a full bridge converter with a multi-winding transformer. By using this transformer the cell equalizing operation can be achieved with no additional circuitry. In addition, a double-line frequency ripple reduction method is proposed to address the low frequency current ripples issues existing in both primary and secondary winding of the transformer which is caused by the voltage ripples across the intermediate DC link bus. Control and analysis of the converter at different operation modes is illustrated in detail and simulation results validate the effectiveness of the proposed converter and control algorithm

User Transmit Power Minimization through Uplink Resource Allocation and User Association in HetNets

The popularity of cellular internet of things (IoT) is increasing day by day and billions of IoT devices will be connected to the internet. Many of these devices have limited battery life with constraints on transmit power. High user power consumption in cellular networks restricts the deployment of many IoT devices in 5G. To enable the inclusion of these devices, 5G should be supplemented with strategies and schemes to reduce user power consumption. Therefore, we present a novel joint uplink user association and resource allocation scheme for minimizing user transmit power while meeting the quality of service. We analyze our scheme for two-tier heterogeneous network (HetNet) and show an average transmit power of -2.8 dBm and 8.2 dBm for our algorithms compared to 20 dBm in state-of-the-art Max reference signal received power (RSRP) and channel individual offset (CIO) based association schemes

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces

A novel non-isolated active charge balancing architecture for lithium-ion batteries

Active charge balancing is an approved technique to implement high performance lithium-ion battery systems. Enhanced balancing speeds and reduced balancing losses are feasible compared to passive balancing. The new architecture proposed in this paper overcomes several drawbacks of other active balancing methods. It consists of only 2 non-isolated DC/DC converters. In combination with a MOSFET switch matrix it is able to balance arbitrary cells of a battery system at high currents. Adjacent cells can be balanced simultaneously. For the given setting, numerical simulations show an overall balancing efficiency of approx. 92.5%, compared to 89.4% for a stack-to-cell-to-stack method (St2C2St, bidirectional fly-back) at similar balancing times. The usable capacity increases from 97.1% in a passively balanced system to 99.5% for the new method

Possibilities and limitations of active battery management systems for lithium-ion batteries

(English) Lithium-Ion Batteries (LIBs) are being used in more and more areas of application. At the same time, their chemical composition and their designs are constantly evolving. Major developments are also taking place in the field of Battery Management Systems (BMSs), which are essential for the safe operation of LIBs. The focus is on intelligent charge redistribution between individual cells, called Active Balancing (AB). This thesis deals with the possibilities and limitations of AB. An empirical long-term experiment provides new insights into the ageing behaviour of batteries that are actively balanced during their entire service life. The main objective of this work is to to demonstrate influences on the ageing behaviour of batteries that are still unknown at present. A literature study shows that previous work in this area is often based on theoretical approaches and rarely has a functional proof through measurement results. Most significant statements from literature are examined. These include the increase in discharge capacity, energy efficiency and service life associated with AB, as well as lower parameter variation of the individual cells installed in the battery. Before starting the empirical experiment, the current state of the art is captured and a universal AB topology is selected from a large number of known systems. The operating behaviour as well as the balancing algorithms are explained in detail in order to be able to understand the influences occurring during the ageing of the batteries. The ageing experiment itself is a comparison test between commercial Passive Balancing (PB) and the novel AB. Two identical battery packs are aged under uniform conditions, but with the two different BMSs mentioned above. At the end of the ageing process, the battery packs are disassembled and the parameters of all individual cells are determined for further investigation. The main contribution of this work is the proof of effects through AB, especially with large battery loads. Both the increase in discharge capacity and the service life are demonstrated. The work shows how parameter variation of individual cells can be made visible during operation. It also presents diagnosis and calculation methods. The energetic efficiency of the batteries cannot be increased, since the self-consumption of the power electronics of the AB system is always higher than with PB. However, the overall efficiency of the battery increases due to an increase in capacity and an extension of the service life. The thesis also shows that with lower battery loads, the use of AB is not beneficial any more or may lead to negative effects. In such applications conventional PB is sufficient. The results obtained during pack ageing are additionally substantiated and extended by the measurement results of the individual cells. At the end of the thesis, all results and contributions are summarised. Suggestions for optimisation as well as further research ideas are presented as a possible starting point for further scientific studies.(Català) Les bateries d’ions de liti (Lithium Ion Batteries, en anglès) s’usen en més aplicacions. Al mateix temps, la seva composició química i dissenys estan en evolució constant. Els sistemes de gestió del bateries (Battery Management Systems, en anglès), que són essencials per l’operació de les LIB, també estan en constant evolució. El focus principal està en la distribució intel·ligent de càrrega elèctrica entre cel·les individuals, l’anomenat balanceig actiu (Active Balancing, en anglès). Un assaig empíric, de llarga durada, com el dut a terme en aquest treball, dona molt informació en el procés d’envelliment de les cel·les durant tota la seva vida. El principal objectiu d’aquest treball és demostrar les influències encara desconegudes en el procés d’envelliment de les cel·les. L’estudi de la literatura mostra que el treball previ en aquesta àrea està sovint basat en aproximacions teòriques i estranyament ensenya resultats empírics que ho corroborin. En aquest treball s’examinen la majoria de presumpcions que es poden trobar a la literatura. Aquestes inclouen l’increment en la capacitat, l’eficiència energètica i la vida útil associada a un balanceig actiu de les cel·les, així com la reducció de la variació dels paràmetres de cada cel·la en una bateria. Abans de procedir amb l’experiment empíric, es revisa l’estat de l’art en els aspectes fonamentals per aquest estudi. També se selecciona una tipologia de sistema de balanceig actiu per tal de realitzar l’experiment. El treball detalla el procediment d’operació així com l’algoritme de balanceig actiu implementat per tal d’entendre els fenòmens que influencien la degradació de les cel·les durant la seva vida. L’experiment d’envelliment és una comparació entre un sistema de balanceig passiu (Passive Balancing, en anglès) i un de balanceig actiu. Per això s’escullen dues bateries idèntiques, però gestionades diferentment per dos sistemes de gestió diferents. Al final de l’assaig, les bateries es desmunten i s’analitza cada cel·la de forma individual per tal de determinar-ne els seus paràmetres i el seu envelliment. La principal contribució d’aquest treball es el demostrar els efectes del balanceig actiu , sobretot en bateries amb una càrrega elevada. El treball demostra que el balanceig actiu millor gla capacitat de la bateria i la vida útil. El treball també mostra com la variació dels paràmetres de les cel·les es pot fer visible durant la seva operació. També presenta nous mètodes de diagnosi i càlcul d’aquests paràmetres. L’eficiència energètica de les bateries no es pot augmentar degut al consum propi i les pèrdues del sistema de balanceig actiu basat en electrònica de potencia. Si que augmenta l’eficiència global de la bateria, ja que augmenta la seva capacitat i la vida útil. El treball també mostra que en bateries sotmeses a baixa càrrega, el balanceig actiu no aporta cap avantatge respecte el balanceig passiu. Fins i tot en algunes situacions, els efectes del balanceig actiu són negatius. En aquestes aplicacions, es recomana l’ús d’un sistema de balanceig passiu. Els resultats obtinguts durant l’assaig de la bateria queden reforçats quan es fa l’anàlisi de cada cel·la de forma individual. Al final del treball, es resumeixen tots els resultats a més de proporcionar suggereixes per la optimització així com possibles línies de futures investigacionsPostprint (published version

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid