Design and implementation of a microcontroller-based adjustable voltage automatic battery charger

This report demonstrates improvements made in battery charging and battery management technology through the design of a universal programmable battery charger with optional battery management system attachment. This charger offers improvements in charge efficiency and unique battery charging algorithms to charge a variety of battery chemistries with variety of power requirements. Improvements in efficiency result from a synchronous Buck Controller topology as compared to previous universal chargers that use asynchronous Buck-Boost Converter topologies. This battery charger also surpasses current universal battery chargers by offering different charge modes for different battery chemistries. Charge modes provide the user an option between extending the life of the battery by selecting a mode with a slower, less stressful charge rate or a shorter charge time with a fast, more stressful charging mode. The user can also choose a charge mode in which the battery charges to full capacity, resulting in maximum runtime or a less than full capacity, which puts less stress on the battery thus extending the lifetime. Ultimately, this system permits weighing the performance tradeoff of battery lifetime and charge time. The optional battery management system attachment offers more precise monitoring of each cell and cell balancing for Li-Ion batteries. This further enhances the performance of the charger when integrated, but is not necessary for charger operation. The battery charger consists of three subcircuits: A microcontroller unit, a power stage, and a current sensing circuit. A C2000 Piccolo F28069 microcontroller controls a LM5117 Buck Controller by injecting a pulse-width modulated signal into the feedback node controlling the output of the buck to set a constant current or constant voltage thus creating a programmable battery charger. The pulse-width modulated signal changes according to charge algorithms created in software for specific battery chemistries and charge requirements. An analog-to-digital converter on the microcontroller monitors battery voltage by using a voltage divider and an INA169 current shunt monitor, which outputs a voltage corresponding to the charge current to another analog-to-digital converter on the microcontroller, monitors the charge current. This allows the charger program to maintain correct and safe charging conditions for each charge mode in addition to measuring output power. Lights on the microcontroller display a real-time status to the user of which portion of the charge profile the charger is in. A solid red light means the charger is in the constant current portion of the charge profile. A blinking red light means the charger

Due to the increasing awareness and adoption of eco-friendly vehicle technologies, hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle (PHEV) technologies have become one of the most interesting areas of research because of the reduced use of fuel and green house emission. Battery chargers are one of the most important parts in developing the HEV's and PHEV's. The various existing optimal battery charging techniques are constant current (CC)-constant voltage (CV) charging, pulse charging and reflex charging. The major problem with these conventional optimal battery charging techniques are that different circuits are needed for adopting different optimal charging techniques. This paper presents design and implementation of a field programmable gate array (FPGA) based versatile optimal bidirectional digital battery charger for HEV/PHEV. The proposed digital optimal charger is capable of adapting all the existing optimal battery charging techniques i.e., constant current-constant voltage (CC-CV) charging, Pulse charging and Reflex charging in a single circuit. The proposed system uses a bidirectional magnetically coupled inductor topology with a damping network. When the proposed system adapts CC-CV charging technique, it shows automatic and smooth transition from CC to CV mode without using any extra switching circuit and when the proposed system adapts pulse and reflex charging techniques it gives regulated charging and discharging currents. Modeling, analysis, and simulation have been carried out on a 250W prototype to validate the proposed algorithm.

State of charge estimation of lead acid batteries is critical for applications that rely on backup power like UPS sytems for telcom operators, data centers, renewable energy installations. Estimating the state of charge of a lead acid battery is a tough job mainly because there is no clear way to predict the behavior of the batteries. One of the common methods of estimation of state of charge of a lead acid battery is by means of measuring the terminal voltage of a lead acid battery. This is not very accurate, but due to its ease of use, it is widely adopted. The current reasearch into estimating the state of charge of a battery is by means of using intelligent control techniques. This paper proposes a methodology by using neural networks. By relying on the parameters of terminal voltage of the battery, load current, temperature of the battery, specific gravity of the electrolyte a methodology is proposed. An Adaptive Neuro Fuzzy Inference System is used here. This system improves the accuracy of the existing methods by using specific gravity when the battery is discharging. The developed topology was tested by using sample data obtained from a manufacturer's datasheet and the benifits of multiparameterized approach was vidicated.

Battery Energy Storage Systems (BESSs) can facilitate renewable energy sources integration onto the grid. For this application, these systems are expected to last for a decade or more, but the actual battery degradation under different real-world conditions is still largely unknown. In this work, three years of lithium titanate BESS usage in Hawai'i were analyzed. In addition, the representative usage was subjected on individual cells under controlled laboratory conditions to study the degradation mechanisms and enable life prognosis. The BESS was found to be operational 90% of the time and it stored a cumulative 1.5 GWh of energy, which represented more than 5000 equivalent full cycles on the cells. From this BESS usage data, an initial estimate of BESS degradation was provided and a representative duty cycle was developed. The analysis of the maintenance cycles indicated that these 5000 equivalent cycles induced an estimated 5-10% degradation of the single cells. The battery duty cycle was characterized based on 5 parameters: pulses duration, pulses intensity (current), state of charge (SOC) swing range, SOC event ramp rate, and temperature. The average usage consisted of several 9-second C/2 charge and discharge pulses organized to generate 5% SOC swings with a 0.75% SOC/min ramp rate at 35°C. However, extreme values such as currents up to 4C, swings of 100% SOC, and temperatures above 50°C were also recorded. Laboratory testing and analysis, in conjunction with a more thorough SOH estimation protocol, resulted in a detailed description of degradation that improved the predictions of the remaining useful battery life. Based on the BESS representative usage profile, cycle-aging and calendar-aging experiments were designed to test the degradation of the associated Li-ion cells in a controlled fashion. It was proven that the cell temperature history had the strongest impact on battery degradation followed by the C-rate and the state of charge. Interestingly, the impact of SOC, both on the cycle-aging and the calendar-aging experiments, was revealed to be counterintuitive. During cycle aging, small SOC swings were more detrimental than larger ones. During calendar aging, batteries lost capacity faster at low SOC than at high SOC. The associated degradation mechanisms and their path dependency were analyzed using incremental capacity analysis.

This paper presents a smart battery charger based on the cascaded boost-buck converter supplied by a photovoltaic (PV) panel. This topology offers a great advantage since it operates in boost mode when the battery voltage is higher than the PV output voltage and operates in buck mode when the battery voltage is lower than the PV voltage output. Due to the presence of inductances at input and output of the cascaded boost-buck converter, the currents across the PV panel and the battery presented very low ripples. In this work, the control of the two converters is simplified since they are driven simultaneously within a same duty cycle. This reduces the implementation cost and complexity. The proposed battery charger operates intelligently; depending on the sun irradiance level and the battery state of charge, the algorithm automatically switches to maximum power point tracking mode, constant current mode, constant voltage mode, or floating charging mode. To verify the overall operation of the system, numerical simulations are performed for two battery voltage levels and including the different phases of charges. According to the obtained good results, the suggested smart charger can be inserted as battery management device in PV energy system.

Lithium‐ion battery as an efficient, sustainable, and clean energy for electric vehicles (EVs) and smart devices becomes more popular with the worldwide demand for reduction of greenhouse gas emission. In all kinds of applications, an accurate real‐time estimation for state of charge (SOC) of battery is necessary. Some conventional methods usually need to sample both battery currents and voltages. This article presents a novel SOC estimation algorithm without current detection. This algorithm just acquires the port voltages of cell to calculate the open‐circuit voltage (OCV) which is related to SOC. By extracting a large number of battery voltages based on a step response, some important parameters that can track battery working process are determined. In order to verify the algorithm feasibility and accuracy, it has been tested on a commercial common field‐programmable gate array (FPGA) in different application conditions. The algorithm accuracy is mainly limited by model accuracy and sampling sensor accuracy. The maximum error between ideal SOC and calculated SOC by this algorithm is within 4%, and the mean error is about 0.99%. So, this high‐feasibility, accredited accuracy, easy integration, and low‐cost solution has bright potential in smarter future.

It is very important to prevent the ships from global environmental pollution and to reduce emissions of greenhouse gases. So it is considered very useful with the object of the prevention of environmental pollution to use hybrid ships which operate by batteries in case of it is near from human habitation and they operate on port district is easy to give off an exhaust is produced by the incomplete combustion by the start and stop of the engine. Therefore, in this report, we consider to navigate by all the batteries when it comes into and leaves a port, and it calculates necessary battery capacity, size and charging time, as an example, it cover the several ships navigates in Tokyo Bay, and we discuss about navigation methods to take on batteries of large capacity. It values at number of a container in the way of the batteries put in a familiar container for the ships as for battery size. This shows between superimposed capacity of the cargos etc and battery size, and it complies battery capacity which mounted, and this report discusses battery about the charge methods and the battery charge time. And it shows practical navigation methods as hybrid ship.

A realistic model for battery state of charge prediction in energy management simulation tools

High Capacity Li-ion and Pb-acid batteries are widely used in present Renewable Energy and EV applications. Consequently, charging these batteries in a minimum amount of time whilst maintaining efficiency is crucial. The need for fast charging has brought up the method of Pulse Charging. However, present pulse charging methods which involve hard-switching, pose problems due to switching losses in the semiconductor devices. This paper presents a Fast Pulse Charging mechanism for High Capacity Pb-acid and Li-ion Batteries which minimizes switching losses by Soft Switching. The operation of the methodology is centered on the Fully Clamped Quasi-resonant DC Link Converter which strategically generates current pulses to charge the battery in both Constant Current (CC) and Constant Voltage (CV) phases. Switching losses are minimized by exploiting Zero Current Switching (ZCS), and the simulated results show that this can be achieved for higher switching frequencies further reducing the circuit size. Experiments were carried out by the research group for both conventional CC-CV method and for current pulse charging method. The results professed that proposed methodology reduces the charging time of Pb-acid batteries by 14.01% in comparison to the conventional CC-CV charging method.

Electric vehicles (EVs) have attracted enormous attention in recent years due to their potentials in mitigating energy crisis and air pollutions. However, the long battery charging time and lack of sufficient charging infrastructure highly restrict the popularization of EVs. In this context, it is promising to establish battery charging and swapping systems (BCSSs) based on the concept of battery swapping services. To optimally achieve the combined operation of BCSSs, this paper proposes a hybrid swapped battery charging and logistics dispatch model in continuous time domain. Identifying the special structure of the mathematical models of the two problems, this paper innovatively formulated the swapped battery charging strategy as the rectangle packing problem and the battery logistics model as the vehicle routing problem. The two models are closely linked by the delivery time of transporting the well-charged batteries from battery charging stations to battery swapping stations. A hybrid optimal operation model of BCSSs is further formulated as a mixed-integer linear programming model by incorporating the interaction between the battery charging and battery logistics. Finally, case studies are conducted on several BCSSs and numerical results validate the effectiveness of the proposed model.

A new battery charge regulator and discharge controller ideal for small (up to 5 Kwp) stand-alone photovoltaic systems, has been designed and developed. This unit is of a Shunt-Switch type and its operation is based on the width modulation of the battery charging current pulses (P.W.M.). It presents an ideal battery charging characteristic (battery voltage and current versus time), because it offers continous battery charging current regulation. For increased reliability, the photovoltaic generator is divided into two subarrays and the battery charging current is controlled through two independent power sections, incorporated in one regulator. Besides, each power section consists of only solid state power semiconductor switches (Power MOSFETs and Schottky power diodes), which are mounted on a large heat sink outside the enclosure, for natural convection. The new unit exhibits a very reliable operation, even at high ambient temperatures. It also possesses two backup protection circuits against battery overcharge, as well as battery deep discharge. The battery voltage is temperature compensated and the maximum/minimum allowable limits, as well as the “load reconnect” battery voltage, are adjustable. The regulator has also been protected against reverse battery connection, short circuits and lightning induced surges.

Stress-regulated pulse charging protocols via coupled electrochemical-mechanical model for the mechanical stability of electrode materials in lithium-ion batteries

This paper presents batteries charger methods using DSP control system. This technique is described that charge a serial string of cell during charging. In this paper, two charge modes have been activated. When a regenerative pulse charger mode starts, the charging current through the string is equal to that of the charging current 10A. If this charge mode ends, the string battery voltage reaches a threshold voltage V T . Then the equalization charge mode starts, thus maintaining the string cell at V T . This circuit topology is composed of two-stage converter, in which the first stage is a bidirectional converter and flyback converter. This charging characteristics (charging time, charging current, switching frequency, and pulse period) of different charging methods are analyzed and presented. The advantage of the hybrid converter CC/CV method is able to reduce the charging time, extend its life, reach 100% battery state of charge and avoid damage to the batteries.

A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles

Low temperature cycling of Li-ion batteries can have two major complications: incomplete intercalation in the anode and lithium metal deposition.1-2 These complications lead to a loss in capacity and cell instability caused by lithium deposits inside the cell. Instability within the cell can cause the battery to begin an exothermic reaction and go into thermal runaway, resulting in a potentially hazardous reaction. Herein we use a pulse charging technique to overcome the limitations associated with low temperature cycling. Commercial 18650 cells were cycled 50 times at 25°C (ambient), 0°C, and at 0°C using a pulse charging technique. The parameters of pulse charge were determined using a single point impedance technique.3 Electrochemical impedance spectroscopy (EIS) was acquired at 10% increments of state of charge (SOC). The frequency least dependent on state of charge indicates a time constant of ion movement where the solid electrolyte interface (SEI) at the anode is least inhibiting to ion flow. Therefore, this frequency was imitated with a square-wave, current pulse to ameliorate the sluggish SEI kinetics often blamed for onset of lithium deposition in low temperature charging. The magnitude of current was prescribed by the cell manufacturer and square pulses were applied until the voltage cutoff was reached. The charge was then topped off with a CV step and constant current discharged in the same manner as the conventionally charged 25°C and 0°C controls. The cells cycled at 25°C remained stable across 50 cycles: staying around 2.6A with 98% capacity retention. The pulsed cell and the cold cell begin with a capacity deficit due to enhanced cell impedance at the cold conditions. The capacity of the cold cell starts to fade, and at the 20th cycle a large drop in capacity is apparent. The drop off in capacity is due to plating of lithium within the cell, which is illustrated in the differential capacity assessment and computed tomography renderings of the cells after charging. The pulses cell does not exhibit fade like the cold cell, maintains a constant capacity, and has an impressive 99% capacity retention at the 50th cycle, which is comparable to the ambient cell. Figure 1. Charge/discharge behavior over 50 cycles for (a) constant current at 25°C (ambient), (b) pulsed charging at 0°C, and (c) constant current charging at 0°C. (d) Capacity retention over 50 cycles for the three charging and temperature conditions. Love, C.; Dubarry, M.; Reshetenko, T.; Devie, A.; Spinner, N.; Swider-Lyons, K.; Rocheleau, R., Lithium-Ion Cell Fault Detection by Single-Point Impedance Diagnostic and Degradation Mechanism Validation for Series-Wired Batteries Cycled at 0 °C. Energies 2018, 11 (4), 834.Love, C. T.; Baturina, O. A.; Swider-Lyons, K. E., Observation of Lithium Dendrites at Ambient Temperature and Below. Ecs Electrochem Lett 2015, 4 (2), A24-A27.Love, C. T.; Virji, M. B. V.; Rocheleau, R. E.; Swider-Lyons, K. E., State-of-health monitoring of 18650 4S packs with a single-point impedance diagnostic. Journal of Power Sources 2014, 266, 512-519. Figure 1