An Optimized Fuzzy Controlled Charging System for Lithium-Ion Batteries Using a Genetic Algorithm

Fast charging is an attractive way of charging batteries; however, it may result in an undesired degradation of battery performance and lifetime because of the increase in battery temperature during fast charge. In this paper we propose a simple optimized fuzzy controller that is responsible for the regulation of the charging current of a battery charging system. The basis of the method is a simple dynamic equivalent circuit type model of the Li-ion battery that takes into account the temperature dependency of the model parameters, too. Since there is a tradeoff between the charging speed determined by the value of the charging current and the increase in temperature of the battery, the proposed fuzzy controller is applied for controlling the charging current as a function of the temperature. The controller is optimized using a genetic algorithm to ensure a jointly minimal charging time and battery temperature increase during the charging. The control method is adaptive in the sense that we use parameter estimation of an underlying dynamic battery model to adapt to the actual status of the battery after each charging. The performance and properties of the proposed optimized charging control system are evaluated using a simulation case study. The evaluation was performed in terms of the charge profiles, using the fitness values of the individuals, and in terms of the charge performance on the actual battery. The proposed method has been evaluated compared to the conventional contant current-constant voltage methods. We have found that the proposed GA-fuzzy controller gives a slightly better performance in charging time while significantly decreasing the temperature increase.

Battery Swapping Station

State-of-the-art research to solve the grid congestion due to EVs is focused on smart charging and using (centralized, de-centralized, vehicle-to-grid) stationery energy storage as a buffer between times of peak and off-peak demand. On the other hand, the charging of EVs introduces new challenges and opportunities. This can prove to be beneficial for the EV aggregator as well as to consumers, regarding the economy. Also, EV as distributed storage makes the grid more steady, secure, and resilient by regulating frequency and the spinning reserve as backup power. However, the charging time and range anxiety lead to peak challenges for the use of EVs. In this chapter battery swapping station (BSS) as solution to the EV charging station is discussed.

Advanced Footstep Power Generation using RFID for Charging

Day by day, the population of the country is increasing and the requirement of the power is also increasing in many ways. So, reforming this energy back to usable form is the major solution for future needs. In this Footstep power generation project, power is generated by human’s footsteps, so as to charge the battery by storing the power generated with the help of piezo sensors. The power stored in the battery, used to charge the mobile phones using RFID card. This system is powered by Atmega 328 microcontroller, it consists of Arduino IDE, RFID Sensor, USB Cable and LCD. When power is on in the system, the system enters into the registration mode. Three users can registered. Once all the users entered in the system, then the system asks to swipe the card and connect the charger. Initially all the user is given 5 minutes of charging time as default. When card is swiped and the user is authorized, the system turns on for charging the Mobile phone within a given time period. Keywords: Arduino Uno, Arduino IDE, Piezoelectric Sensors, RFID (Radio Frequency Identification ), LCD

Optimization of a Mobile Energy Storage Network

This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To this end, a series of degradation tests were carried out on lithium-ion batteries, in four different charger regimes, in which the battery voltage amplitude and the charging electric current were varied. The results of these tests were incorporated into the optimization model as the depreciation rate and charge time over battery life. The mathematical modeling innovates by including new components designed specifically for this new problem: battery availability according to charging time; different types of customer service; objective function modeling that includes the logistical costs of battery relocation, terminal maintenance, and battery depreciation. The results indicate that the network performance using batteries in the fastest charging configuration tends to have a positive impact on their efficiency and profitability. The model can be used as a reference for other applications that require recharge points that enable the use of mobile batteries, such as electric scooters, electric bicycles, and drones, among others.

Design of high speed 2-stage OTA for high capacitive load of 120pF and 2.96V

High speed operational transconductance amplifier (OTA) is used to drive high capacitive loads to reduce the charging time while providing adequate gain and stability. A 2-stage amplifier is proposed to provide high slew rate and sufficient gain and stability. 45nm process technology is used to compare performance with differential and telescopic amplifier designs. Resistive feedback and noise-gain compensation techniques are used to drive 120pF load and provide 2.96V at output for a high slew rate of 2.2V/µs.