enable different battery charging algorithms to be tested under the same operating conditions. The main parameters in a photovoltaic system are solar radiation,.
Comparison of Battery Charging Algorithms for Stand Alone Photovoltaic Systems S. Armstrong*, M.E. Glavin*, W.G. Hurley* *
Power and Energy Research Center, National University of Ireland, Galway
Abstract— The battery is the most common method of energy storage in stand alone solar systems; the most popular being the valve regulated lead acid battery (VRLA) due to its low cost and ease of availability. Photovoltaics are not an ideal source for charging batteries as their output is heavily dependent on weather conditions. Therefore, when batteries are used in photovoltaic systems, the performance characteristics differ significantly from batteries used in more traditional applications and the battery life is usually shortened. In conditions of varying solar radiation and load profile the battery may experience a low State of Charge (SOC). A low SOC for extended periods of time will cause increased sulphation, which severely reduces the life of the battery. Typically, steps are carried out to protect the battery and to charge the battery more effectively. Such methods include Intermittent Charging (IC), Three Stage Charging (TSC) and Interrupted Charge Control (ICC), among others. This paper quantifies the effectiveness of these three battery charging algorithms and evaluates their ability to maintain the battery at a high state of charge. The measurement setup is comprised of a solar simulator, which replicates the output of a large 50W photovoltaic panel using a low power cell. Repeatable load and solar radiation profiles and temperature control are implemented using LabView so that identical operating conditions can be set up to compare the three battery charging systems.
I.
Their performance is monitored using a solar simulator management system with programmable solar radiation, temperature and load profile. The paper is divided into the following sections; first, the solar simulator management system is introduced. The battery charging algorithms used for comparison are then discussed and experimental results for the battery charging profiles, temperature and state of charge are presented. II. SOLAR SIMULATOR MANAGEMENT SYSTEM Photovoltaic applications are subjected to randomly fluctuating atmospheric conditions, making the testing of a battery management system in real weather situations both costly and time consuming. The use of a solar simulator system provides a low cost solution, generating reliable results, which can replicate actual weather conditions. These reproducible conditions enable different battery charging algorithms to be tested under the same operating conditions. The main parameters in a photovoltaic system are solar radiation, temperature and load conditions. A solar simulator management system has been developed to simulate these variables. Several solar simulators have been previously described. In [9] predetermined solar parameters are loaded into a lookup table using EPROM and a regulator produces the required output voltage. The solar cell’s characteristic equations may be implemented by a microcontroller under varying operating conditions [10-12]. Solar simulators have also been based on the equivalent model using a current source in parallel with a diode [13].
INTRODUCTION
A typical photovoltaic system consists of a solar panel, regulator, battery and load [1-3]. Of all these components, it had been shown that the battery may account for up to 40% of the overall system cost over its lifetime [4]. Batteries in photovoltaic systems are subject to performance losses that are caused by limited availability of time and energy to recharge the battery and inadequate battery maintenance. In most applications, batteries are undercharged [5-8]. Extended periods of undercharging leads to sulphation and stratification, which reduces the effectiveness of the battery and shortens its lifetime. Overcharging the battery causes gassing and grid corrosion, which also shorten the battery life. Three battery charging algorithms are investigated to determine their effectiveness at maintaining the battery at a high state of charge and increasing the life cycle of the battery.
978-1-4244-1668-4/08/$25.00 ©2008 IEEE
The proposed solar simulator is more accurate for temperature and solar radiation control in a fully automated system controlled by LabView. The block diagram of the solar simulator management system is shown in Fig. 1. The main components are the solar simulator and dc-dc converter. These are described in more detail in the following section.
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III.
BATTERY CHARGING ALGORITHMS
The three battery charging techniques used for comparison are Intermittent Charging (IC) [15], Three Stage Charging (TSC) [16] and Interrupted Charge Control (ICC) [17] as illustrated in Fig. 3 (a)-(c). A. Intermittent Charging
Fig. 1: Diagram of proposed solar simulator
A. Solar Simulator The purpose of the solar simulator is to amplify the output of a low power cell (17mW) to reproduce the voltage and current characteristics of a typical 50W solar panel. The operation is based on a power amplifier with output current feedback. A stationary DC halogen lamp, whose brightness is adjustable and programmed through LabView, is used to illuminate the solar cell. Sensors measure the cell temperature and solar radiation. Temperature control of the cell is carried out to produce repeatable testing. The currentvoltage (I-V) and power-voltage (P-V) characteristics are shown in Fig. 2. A standard Buck dc-dc converter is incorporated into the solar simulator to implement maximum power point tracking (MPPT) using the Incremental Conductance method. A buck converter is used in these experiments instead of the more commonly used boost converter in photovoltaic systems because the voltage output of the 50W solar simulator exceeds the voltage requirements of the 12V battery used for testing. The output of the dc-dc converter is connected to an electronic load and a 12V 16Ah lead acid battery.
I-V
P-V
Fig. 2: Solar simulator output I-V axis: y-axis 1 A/div, x-axis 2.5V/div P-V axis: y-axis 20W/div, x-axis 2.5V/div
Intermittent charging, (IC), as shown in Fig. 3(a), is the most commonly used method in commercial chargers. The battery is charged with maximum power point tracking (MPPT) between two predefined voltage thresholds. When the battery reaches the upper voltage threshold, VUT, the charging is stopped and the battery is kept in open circuit. The battery voltage is monitored until it drops to the lower voltage threshold, VLT, when the charging begins again. B. Three Stage Charging Three Stage Charging (TSC) delivers power to the battery in three steps as shown in Fig 3(b). The first step is bulk charging. The battery is charged at maximum current using maximum power point tracking until the battery reaches its final charging voltage, known as the absorption voltage. This step replaces 70-80 % of the battery's capacity at the fastest possible rate. The battery is kept in this mode until the charge voltage reaches the upper voltage threshold, typically 14.2V. The second step is absorption charging. The charging current is steadily decreased while the battery voltage is maintained at the absorption voltage. This step replenishes the remaining 20-30% of capacity. The final stage is float charging. A small current is supplied to the battery to maintain the battery voltage. The overcharging current induces water loss at the negative electrode of the battery and grid corrosion at the positive electrode, which have a detrimental effect on the service life of the battery. C. Interrupted Charge Contol The third battery charging algorithm used for comparison is the Interrupted Charge Control (ICC), as shown in Fig. 3(c), which is a variation of the Intermittent Charging described in III (A). ICC avoids the potential undercharging problem faced by the IC method. This approach charges the battery in four modes. In Mode I, the battery is charged with constant current with a charge rate of 0.1C to an upper threshold and then left in open circuit until the lower threshold limit is reached (Mode II). The battery is then pulse charged with a charge rate of 0.05C until the upper voltage limit is reached again (Mode III). These are the charge rates chosen for optimum operation. The battery is then left in open circuit and is at full capacity (Mode IV). A full charge return is ensured. Modes I - III are repeated when the battery voltage falls to 97% state of charge. The ICC regime has been shown to be particularly suitable for standby applications [17].
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Fig. 3(a): Intermittent Charging
Fig. 3(b): Three Stage Charging Fig 5: Example of the two pulse test for state of charge detection
B. Fig. 3(c): Interrupted Charge Control
IV.
State of Charge Two Pulse Test
In order to properly compare the battery charging algorithms, identical starting conditions need to be established. The state of charge (SOC) of the batteries are determined by a two pulse method described in [18]. The SOC of a battery is defined as the ratio of the dischargeable Ampere-hour to the current Amperehour capacity of the battery. The starting SOC of each battery was set as 65%. A screenshot of the two pulse technique is shown in Fig. 5. The battery is first left in open circuit for a minute so that it may recover from any recent load activity. Two current pulses of 12.5A are supplied to the battery with a duty cycle of 33%. The first pulse is responsible for stabilising the battery relative to its previous history or activity. The second pulse establishes the parameters necessary to determine the state of charge. The voltage of the battery at the beginning and end of the second pulse, Vmax and Vmin respectively are used to determine the state of charge of the battery.
EXPERIMENTAL SETUP
A. Battery Managment System The experimental setup for the solar simulator management system is shown in Fig. 4. The user may control the choice of battery charging algorithm, solar radiation and load control for every hour of a particular day. Accurate and automated control of the radiation, temperature levels and load profile allows testing over a wide range of operating conditions and permits repeatable patterns of temperature and radiation to provide a platform to compare the various charging algorithms. The solar simulator outputs and the battery’s voltage, current, temperature and state of charge are recorded by LabView to ascertain the ability of the charging algorithms to maintain the battery at a higher state of charge.
Fig. 4: Experimental Setup
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V.
EXPERIMENTAL RESULTS
A. Charging Profiles The charging profiles of the Intermittent Charging, Three Stage Charging method and Interrupted Charge Control method are shown in Fig. 6, 7 and Fig. 8 respectively. These are the resultant charging profiles from the solar radiation pattern shown in Fig. 9. The operating parameters for each charging algorithm are shown in Table 1.
TABLE I. Fig. 6: Intermittent Charging profiles
Charging Algorithm
Important Parameters
Intermittent Charging
Upper Voltage Threshold: 14.2V Lower Voltage Threshold: 12.84V
Three Stage Charging
Upper Voltage Threshold: 14.2V Lower Voltage Threshold: 13.2V
Interrupted Charge Control
Upper Voltage Threshold: 14.7V Lower Voltage Threshold: 13.0V
In Intermittent Charging (IC) in Fig. 6, the lower and upper voltage thresholds are recommended by [19]. At this threshold, the battery is charged to 95% state of charge. The choice of the upper and lower threshold limits need to be chosen carefully because if the parameters are too close together then the charging will begin too early and it will operate close to float charging. If the parameters are chosen too far apart then the battery will discharge to an unacceptable low state of charge. Under a simulated solar day, the lower voltage threshold is not reached as the VRLA battery takes longer than twenty hours to drop to this threshold. The rate of the voltage drop depends on the age of the battery; an older battery with a lower state of health will have a higher rate of self-discharge.
Fig. 7: Three stage charging profiles
Fig. 8 shows the charging profile of the ICC method. The battery charging current is maintained at 0.1C (1.6A for a 16Ah battery) until the upper voltage threshold is met (Mode I). At this stage, the battery is left in open circuit and the battery is at 98% SOC (Mode II). Under the simulated solar day, the battery voltage does not fall to 13.0V; therefore the battery remains in Mode II.
Fig. 7 shows the charging profiles of the Three Stage charging method. This charging method brought the battery to 100% state of charge at the end of the day.
Fig. 8: ICC charging profile
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Evidently, the Three Stage Charging algorithm restores the battery to 100% SOC in the quickest time, although some overcharge is apparent. Intermittent Charging restores the battery to 95% SOC but the battery remains in this state as the battery will take over twenty four hours to drop to the lower voltage threshold under no load conditions. The ICC charges the battery to 98%. Similarly, the battery remains at this point as the battery is also left in open circuit. This charging algorithm takes longer to reach the same level of SOC because the battery charging current is limited to 1.6A (0.1C) whereas the other two algorithms use the maximum solar panel current available by incorporating maximum power point tracking.
Fig. 9: Solar simulator measurements over the course of a simulated day
B. Variable Load Profiles The performance of the battery under a varying load profile was also investigated. The load profile is shown in Fig. 10, featuring high load demand in the morning and afternoon. The effect of the varying load profile on the battery’s SOC will be demonstrated in Section V.
Fig. 11: SOC of the charging algorithms over the day (under no load conditions)
Fig. 12 shows the state of charge of the battery under the varying load profile shown in Fig. 10. Once more, the Three Stage Charging method returns the battery to full state of charge in the quickest time possible. The Intermittent Charging algorithm also fully recharges the battery, although some overcharging occurs. This is because the choice of the voltage threshold does not correspond to the 100% state of charge condition. The voltage at which overcharging begins is dependent on the charge rate which varies due to atmospheric conditions [19]. When the battery voltage drops below the lower voltage threshold, maximum power point tracking is implemented. This delivers all the available current to the battery that is not required by the load, causing overcharging. The jagged edge in the Intermittent Charging SOC curve is caused by the frequent transition between Mode 2 and Mode 3, where the battery is constantly connected and disconnected. The overcharging caused by the Three Stage Charging method is less significant because the charging current has been decreased in Mode 2 and 3. The SOC is lowest for the Interrupted Charge Control method. Mode 1 limits the battery charging current to 1.6A therefore the charging algorithms is unable to restore the charge to the battery that has been drawn by the load and always remains in Mode I.
Fig. 10: Variable load profile
V. COMPARISON OF THE BATTERY CHARGING REGIMES In this section, the three battery charging algorithms are compared under different criteria; the ability to maintain the battery at a high state of charge, charging efficiency and effect of charging algorithm on the battery’s temperature. A. State of Charge The performance of the three battery charging algorithms was first investigated under no load conditions. Figure 11 shows the state of charge of the battery under each battery charging algorithm.
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C.
Temperature effects
The battery temperature was also monitored to investigate the effect of the different charging algorithms. The operating temperature has a profound effect on the battery. It affects the chemical reactions of the battery which in turn determines the amount of useable charge available. For every 10 degree rise in temperature, the chemical reaction rates double, leading to possible thermal runaway and more rapid self discharge [17]. Temperature compensation may be implemented to correct the voltage thresholds and charge rates of the charging regimes in order to avoid overcharging or undercharging the battery [20]. Fig. 12: SOC under varying load profile
B. Charging Efficiencies Fig. 13 shows the charging efficiencies of the three different charging algorithms under no load. The charging efficiency is determined by the fraction of solar energy available that is supplied to the battery. Energy is supplied to the battery at a rate which is determined by the battery’s state of charge. The starting state of charge of the battery is identical for each charging algorithm and each one is subjected to the same operating conditions so that charging efficiencies can be compared. The experimental results show that the Three Stage Charging method has the highest efficiency over the course of the day. The Intermittent Charging method shows high efficiency as it recharges the battery to 95% SOC but once this condition has been reached, the battery is disconnected and the solar energy available is not fully utilized. Similarly, the efficiency of the Interrupted Charge Control Method is decreased when 98% SOC has been reached. The overall efficiency of this algorithm is the lowest as the full solar panel current is not utilized.
The charge rate of the battery charging algorithms determines the temperature response of the battery. The temperature response of the battery under the three different charging algorithms is shown in Fig. 14. Evidently, the Three Stage Charging method results in the highest temperature rise. The float voltage is present across the battery terminals even after it is fully charged. A high percentage of the float current goes into overcharge which can cause grid corrosion and potential gassing. The Intermittent Charging algorithm shows a rise in battery temperature until the upper voltage threshold is met. At this point the battery charger is disconnected; therefore the temperature begins to drop. The ICC charging algorithm results in the lowest average battery temperature due to the fact that the majority of the charge is returned to the battery at a charge rate of 0.1C in Mode 1, whereas the other two algorithms use maximum power point tracking. The peak temperature occurs when the SOC is equal to 98% and subsequently begins to drop. This lower operating temperature is beneficial in prolonging the lifespan of the battery.
Fig. 14: Battery temperature during the different charging algorithms
Fig. 13: Comparison of the charging efficiencies (under no load conditions)
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2nd World Conference and Exhibition on Photovoltaic Solar Energy Conversion, Vienna, pp. 3266-3268, 1998. [6] P. Diaz, M.A. Egido, “Experimental analysis of battery charge regulation in photovoltaic systems.” Progress in Photovoltaics: Research and Applications, Vol. 11, No. 7, pp. 481-493, November 2003. [7] H. Yang, H. Wang, G. Chen, G. Wu, “Influence of the charge regulator strategy on state of charge and lifetime of VRLA battery in household photovoltaic systems”, Solar Energy, Vol. 80, pp. 281287, March 2006. [8] J. Garche, A. Jossen, H. Doring, “The influence of different operating conditions, especially over-discharge, on the lifetime and performance of lead acid batteries for photovoltaic systems.” Journal of Power Sources, Vol. 67, pp. 201-212, August 1997. [9] S.H. Lloyd, D.G. Infield, "Design and construction of a modular electronic photovoltaic simulator", Power Electronics and Variable Speed Drives Conference Proceedings, No. 475, pp: 120-123, 2000. [10] K. Kachtsevanos, G. Vachtsevanos, "A hybrid photovoltaic simulator for utility interactive studies", IEEE Transactions on Energy Conversion Vol. 2, pp: 227-231, 1987. [11] J. Yoo. J. Gho, G. Choe, “Analysis and control of pwm converter with v-i output characteristics of solar cell”, IEEE International Symposium on Industrial Electronics (ISIE) Proceedings, Vol. 2, pp: 1049-1054, 2001. [12] K. Khouzam, K. Hoffman, “Real-time simulation of photovoltaic modules”, Solar Energy, Vol. 56, No. 6, p. 521-526, 1996. [13] Appelbaum, J. “Starting and steady-state characteristics of DC motors powered by solar cell generators”. IEEE Transactions on Energy Conversion, EC-1, pp: 17-23, 1986. [14] F. Huang, D. Tien, J. Or, “A microcontroller based automatic sun tracker combined with a new solar energy conversion unit”, Proceedings of the International Conference on Power Electronics Drives and Energy Systems for Industrial Growth, Vol. 1, pp: 488 – 492, 1998. [15] P. Waltari, T. PSuntio, A. Tenno, R. Tenno, “The effects of intermittent charging on VRLA battery life expectancy in telecom applications”, 24th Annual International Telecommunications Energy Conference, pp: 121-127, 2002. [16] www.xantrex.com [17] M. Bhatt, W.G. Hurley, W.H. Wolfe, “A new approach to intermittent charging of valve regulated lead acid batteries in standby applications”, IEEE Trans. on Indust. Electronics, Vol. 52, 5, 2005. [18] M. Coleman, C.K. Lee, W.G. Hurley, “State of health determination: two pulse load test for a VRLA battery”, 37th IEEE Power Electronics Specialists Conference, 2006, pp: 1 – 6. [19] E. Koutroulis, K. Kalaitzakis, “Novel battery charging regulation system for photovoltaic applications”, IEEE Proc. Power Appl, Vol . 151, No. 2, pp: 191-197, 2004. [20] Y.S. Wong, W.G. Hurley, W.H. Wölfle, “Temperature compensation algorithm for interrupted charge control regime for a VRLA battery in standby applications”, 23rd IEEE Applied Power Electronic Conference, 2008.
The experimental data shown has demonstrated that the Three Stage Charging method is the most suitable battery charging algorithm for a photovoltaic system. This method returns the most charge to the battery in the quickest time without causing a significant rise in the battery temperature. The peak temperature of the Three Stage Charging method is only one degree higher than the Intermittent Charging peak temperature. The Interrupted Charge Control method is less effective at returning the battery to a full state of charge than the other two algorithms. However, the operating temperature of the battery is lower which aids in prolonging the life of the battery. Under regularly cycled conditions, ICC method does not reach Mode III, therefore the full benefits of this regime are not exploited. Mode III reduces the degree of overcharging experienced by the other charging regimes and provides equalization of the cell voltages in a string of batteries. The results suggest that this charge regime would be better utilised in a standby application. VIII.
CONCLUSIONS
The Three Stage Charging method has been established at the most suitable battery charging algorithm for a regularly cycled battery in a photovoltaic system. A fully automated solar simulator management system was used to accurately compare the performance of battery charging algorithms during varying atmospheric and load conditions.
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