Control Strategy for Battery-Ultracapacitor Hybrid Energy Storage System F. S. Garcia*, A. A. Ferreira**, and J. A. Pomilio*** *
**
University of Campinas, Campinas, Brazil. Email:
[email protected] Federal University of Pampa, Alegrete, Brazil. Email:
[email protected] *** University of Campinas, Campinas, Brazil. Email:
[email protected]
Abstract—Hybrid energy storage systems have been investigated with the objective of improving the storage of electrical energy. In these systems, two (or more) energy sources work together to create a superior device in comparison with a single source. In particular, batteries and ultracapacitors have complementary characteristics that make them attractive for a hybrid energy storage system. But the result of this combination is fundamentally related to how the sources are interconnect and controlled. The present work reviews the advantages of batteryultracapacitor hybridization, some existing solutions to coordinate the power flow, and proposes a new control strategy, designed for the improvement of performance and energy efficiency, while also extending the battery life. The control strategy uses classical controllers and provides good results with low computational cost. Experimental results are presented.
I. INTRODUCTION "Energy is central to achieving the interrelated economic, social and environmental aims of sustainable human development. But if we are to realise this important goal, the kinds of energy we produce and the ways we use them will have to change [1]." The great advance in battery technology, fueled by nanotechnology [2-5], and economical and environmental pressures, have opened a road to commercially viable battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), as indicated by the growing investment of established and start-up automotive companies [6-8]. This movement represents an important step toward a sustainable transportation system. Still, further improvement of the energy storage system (ESS) is a key factor for the wide adoption of electric vehicles (EVs). In order to accomplish this goal, it has been investigated the impacts of the integration of two (or more) energy sources, with the objective of attaining the best characteristics of each, producing a hybrid energy storage system (HESS) [9]. However, the degree of improvement of a HESS, compared to a single-source ESS, depends intrinsically on how the sources are combined to exploit the strengths and avoid the weaknesses of each source. As batteries, ultracapacitors are evolving rapidly and costs are declining [10-12]. A promising path is using ultracapacitors to complement the action of batteries [9, 13]. Commercial scale products have already started to consider this combination [14-15].
Keywords—Battery; Control systems; Power electronics; Road vehicle electric propulsion; Ultracapacitor.
NOMENCLATURE Battery terminal voltage Ultracapacitor terminal voltage Battery converter output current Ultracapacitor converter output current Battery converter input current Ultracapacitor converter input current Load current ("motor") Total current entering DC link Output voltage Above variables are functions of time. When they appear in uppercase, Laplace transform is indicated. When they are followed by an asterisk, a reference value is represented.
II.
A. Power versus Energy The power demanded by an EV is very variable. Peak power occurs at acceleration and braking, which happens for a short time, compared to the whole driving cycle. The ratio of the peak power to average power can be over 10:1 [13]. Within the available technology, there is a trade-off between specific energy and specific power, as shown in Ragone plot of Fig, 1. Even for a given battery chemistry, it is usually possible to optimize the cell design for better specific energy or for better specific power. Combining batteries and ultracapacitors can create, for applications with high peak-to-average power, a virtual source with high specific energy and high specific power.
Battery series resistance Input capacitor of battery converter Inductance of battery converter inductor Resistence of battery converter inductor Ultracapacitor capacitance Ultracapacitor series resistance Input capacitor of ultracapacitor converter Inductance of ultracapacitor converter inductor Resistence of ultracapacitor converter inductor Output capacitor
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REASONS FOR BATTERY-ULTRACAPACITOR HYBRIDIZATION
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Specific Energy (Wh/kg)
D. Batteries life Ultracapacitors have a very long life, significantly higher than batteries. As the battery cost is significant in the price of the whole car, the life of batteries is very important to customer acceptance of EVs. High charge or discharge rates shorten the battery life, including high current-rate lithium-ion batteries [22, 23]. Reference [24] analyses the life reduction of cobalt-based lithium-ion cells for high charge or discharge current. E. Temperature Range Ultracapacitors can operate under a wider temperature range than batteries [14]. When used together, ultracapacitors can attenuate the reduction in the power available from batteries in extreme temperature conditions. Figure 1: Ragone plot
III.
B. Higher Energy Efficiency "Delivering high power for a short period of time is deadly to batteries, but it is the ultracapacitor strongest suit [16]." As the ultracapacitor is able to deliver or receive energy in peak power situations, it can act as a load-leveling device for the battery. If this is done, the battery demand would become closer to the average power demand, thus reducing its RMS and peak currents. The relationship of the discharge time and discharge current in a battery can be modeled by Peukert capacity [17], T
A. Parallel Connection A simple solution to integrate a battery and an ultracapacitor is to connect them in parallel. The different dinamic behavior of battery and ultracapacitor will determine the current distribution between sources. This connection results in a reduction of current peaks in the battery [25, 26], and improvement of battery life and efficiency is expected [27]. Nonetheless, these results can be improved when the ultracapacitor is connected through a converter and its voltage is allowed to a much wider range. If voltage is restricted by battery most stored energy becomes unavailable [9, 28].
(1)
B. Rules and Reference Tables Many variations of control strategies that uses rules or reference curves and tables have been proposed. Reference [29] proposes to calculate the total power demand and, with this information, use a set of rules to divide the power between battery and ultracapacitor. For example, in a given situation, all the power demand exceding a threshold would be supplied by the ultracapacitor. In [30], the ultracapacitor state of charge (SoC) is determined by the speed of the vehicle and the battery SoC. This strategy is designed so the ultracapacitor is discharged as the vehicle accelerates (and vice-versa), reducing the peaks in power demand related to accelaration and braking. Reference [31] concludes that an battery-ultracapacitor HESS using a similar strategy is not viable from a lifecycle cost perspective. In [32] the different rules (for example, battery supplies power to the load and to rechage the ultracapacitor) are selected by the use of a flowchart that takes into consideration the state of charge of the sources and the load demand.
In (1), is the Peukert capacity (which is a characteristic of the battery being analyzed), I is the discharge current, T is the discharge time, and is the Peukert coefficient (usually 1.1-1.3 for lead acid, and 1.05-1.2 for nickel metal hydride and lithium ion [18]). As a consequence of (1), battery delivers less charge (the integral of current) when discharged faster. As the terminal voltage is lower for higher current – on account of the internal resistance – the energy delivered is still reduced. Reference [19] compares the reduction of energy with increased discharge current for different lithium-ion chemistries. Reference [20] relates the reduction of energy efficiency of a lithium battery with increased discharge current. Reference [21] shows that pulsed discharge profile results in increased cell temperature, considering the same average current. C. Regenerative braking According to [13], the energy involved in the acceleration and deceleration transients is roughly two thirds of the total amount of energy over the entire mission in urban driving. Therefore, increasing the energy recovered by regenerative braking has a great potential to extend the range of an electrical vehicle. Charge current in batteries are limited to a smaller value compared to discharge current. This characteristic limits the energy that can be recovered by regenerative braking. Ultracapacitors may have an important role in braking situation, because they can be charged very fast and their life is, to a much higher degree in comparison with batteries, insensitive to charge/discharge profile.
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REVIEW OF SOME EXISTING SOLUTIONS
C. Fuzzy Logic Control Fuzzy logic control was used to the specific problem of controlling a hybrid energy storage system with good results in [33]. It does not demand a precise model of the plant because it is based on designer's knowledge on it, what is an important advantage when a model is not available. Reference [34] applies fuzzy logic control together with management methodology to the problem of controlling a batteryultracapacitor HESS.
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IV.
PROPOSED SOLUTION
D. Ultracapacitor Voltage Control The control of the battery converter input current reference (i ) is done based on the ultracapacitor voltage . For this, the complete control diagram of the system presented in Fig. 3 is used. At this point, only the load current (i ) is treated a perturbation and all other variables become part of the model. Based in the control diagram of Fig. 3, the transfer function that relates the ultracapacitor voltage with the reference of current in the battery is, as demonstrated in Appendix I,
A. Topology The battery and ultracapacitor are interconnected using electronic converters with bidirectional current capability, as shown in Fig. 2. The same topology is used in other works, for example in [35]. Reference [36] compares this topology with others.
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The transfer function of (2) expresses how the batteryconverter input-current reference affects the ultracapacitor voltage. But it is interesting to notice that there is not a "direct" influence: these variables are linked by the action of the controllers previously implemented, as can be understood by the control diagram of Fig. 3. This transfer function allows the synthesis of a controller for ). This controller is responsible ultracapacitor voltage ( for restoring the ultracapacitor voltage to the reference level ( ). Its bandwidth is limited to a frequency much lower than ), consequently the the output voltage controller ( ultracapacitor is the first device to be affected by a change in load demand. Only after the ultracapacitor voltage is disturbed, battery current will be adjusted to restore ultracapacitor voltage to the reference level ( ). This difference in the bandwidth of the voltage controllers results in a rejection of power peaks by the battery. As the control action restores ultracapacitor voltage, ultracapacitor operates in a charge-sustaining mode, that is, it can be charged or discharged until its limits, but after transients its voltage will be brought back to the reference level ( ).
Figure 2: Connection of battery and ultracapacitor
B. Current Inner Loop The first step is to control the input current of the converters with an inner control loop (as done in current mode control converters [37]). For this, it is needed a model relating the input current of each converter and the control variable (for example, the duty cycle for a PWM converter). In Fig. 3, the model of the plant that relates the input current of the ultracapacitor converter with the control variable of this . The current controller of ultracapacitor converter is . This closed loop current control is in converter is region 1 and, when necessary, the closed loop response of this . region is represented by Again in Fig. 3, the model of the plant that relates the input current of the battery converter with the . The control variable of this converter is . This current controller of battery converter is closed loop control is in region 2 and, when necessary, the closed loop response of this region is . represented by C. Output Voltage Control The following step is to implement the output voltage controller ( ). The ultracapacitor ) is used to converter input current reference ( regulate the output voltage ( ) at the reference level ( ). In this step, the load current ( ) and the battery) are treated as converter output current ( perturbations. The control diagram for output voltage control is shown in Fig. 3, region 3. The use of the ultracapacitor current to control the output voltage results in a fast response and stable DC-link voltage for inverter. Because of this controller action, the ultracapacitor current can change very fast to supply load demand. This same control loop was used in [33] and [35].
Figure 3: Control diagram
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In Fig. 5, the battery is modeled as an ideal voltage source with a series resistance, and the ultracapacitor is modeled as an ideal capacitor with a series resistance. The values of components are presented in Table I.
V. RESULTS Fig. 4 shows the experimental set-up. The control algorithm is implemented in an Analog Devices 16-bit DSP (ADSP21992). The DSP and signal conditioning boards are in position A. The hardware (B) used to implement the converter is a Semikron four-leg (each leg composed by a SKM50GB123D IGBT module) inverter bridge module. One leg is used for battery converter, another for ultracapacitor converter, another for overvoltage protection and the other one is not used. Inductors are enclosed in a metal box (C), for reduction of EMI. A resistive load (D) is used to simulate the load. Twelve series-connected lead-acid batteries, rated 12V, 2.2Ah each, totaling 144V, 2.2Ah and five series-connected ultracapacitors modules made by Maxwell Technologies, rated 42V, 150F each, totaling 210V, 30F were used (E).
TABLE I. VALUES OF COMPONENTS
940 1.5Ω 470 1.7 700 Ω
30 80 Ω 470 1.2 300 Ω
For the modeling of converters, state space averaging technique was used, which consists in writing the state space equations of the circuit for each possible configuration of the switches, than average the matrices of the system pondered by the time spent in each state [39]. The modeling of these converters indicates a non-minimum phase system (that is, with a zero on the right-half plane). Current mode control attenuates this characteristic, because the output loop has a smaller bandwidth than the current-control loop, and the order of the system is reduced. The two current controllers (with bandwidth of 1 kHz) and the output voltage controller (with bandwidth of 100 Hz) were designed using the k-factor method [40]. At this point only this three of the four controllers presented in Fig. 3 are active on the DSP. To validate the correction of the model, the transfer function of (2) was experimentally measured. This measurement was accomplished using a signal generator (F) to generate a sinusoid acquired by the DSP and used as battery current reference. In this experiment, all controllers are active, except . Magnitude and phase of reference and of for consequent perturbation in ultracapacitor voltage were measured using an oscilloscope. The experimental result is compared to model prediction in Fig. 6.
Figure 4: Experimental set-up
For the modeling, simulation and experimental implementation a half bridge topology (also called bidirectional boost or buck-boost in literature) was used, as show in Fig. 5. The converters operate with PWM modulation and the switching frequency was set to 10 kHz. The driving of the power switches of each converter is complementary; consequently the converters are always in continuous conduction mode.
Figure 5: Converters topology Figure 6: Model validation with experimental data
Except for the modeling of the converters, the control strategy presented in this paper is applicable to other converter topologies. Reference [38] presents alternatives and compares some topologies.
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The agreement of mathematical modeling and experimental data indicates accuracy of the model and also that the three active controllers are behaving as expected.
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With the model of Fig. 3 validated, a controller for ultracapacitor voltage was designed, using the transfer function of (2). Its bandwidth was set to 0.1Hz, much below than the output voltage controller bandwidth, which operates at 100Hz. Besides regulating the output voltage and restoring ultracapacitor voltage, it is very important to determine how the power demand is distributed between the sources. For this, the transfer functions relating output current of converters and load current were calculated based on control diagram of Fig. 3 (as shown in Appendix II), and their magnitude are presented in Fig. 7. Now, all four controllers are operating.
In the experiment shown in Fig. 9, the load was turned on and off several times in cycles of about 2 seconds (channel 2). If there was only a battery, its current would have to repeat the same pattern. But, as the ultracapacitor supplies high frequency components (channel 4), the current supplied by the battery corresponds roughly to the necessary to supply the average power (channel 3). The output voltage remained stable (channel 1).
Figure 9: More experimental waveforms Figure 7: Transfer function of selected currents to load current
As a limitation of the experiments performed, it should be noted that the use of a resistive load does not allow the emulation of a driving cycle neither the recovery of energy as it happens in regenerative braking.
Transfer functions plotted in Fig. 7 demonstrates that lowfrequency (up to ultracapacitor-voltage-controller cutoff frequency) components of load current are supplied by the battery while high frequencies (from ultracapacitor-voltagecontroller cutoff frequency to output-voltage-controller cutoff frequency) are supplied by the ultracapacitor. With all controllers implemented on the DSP, the system was tested with a resistive load. In the experiment shown in Fig. 8, the resistive load was turned on for about 4 seconds (its current is shown in channel 2). The output voltage remained stable (channel 1) by the fast action of the ultracapacitor current (channel 4). The current on battery (channel 3) changes slowly, as expected by low-pass-filtering action demonstrated in Fig. 7.
VI. CONCLUSIONS The battery-ultracapacitor hybridization can bring significant benefits to electric vehicles, due to the high peakto-average power demand of this application and the complementary characteristics of batteries and ultracapacitors. A new control strategy to coordinate the power flow was presented. The strategy can be implemented with low computational cost. In a nutshell, the proposed control strategy regulates the output voltage and restores ultracapacitor voltage after transients. It divides the power demand into low-frequency components and high-frequency components. The lowfrequency components are supplied by the battery, while highfrequency components are supplied by the ultracapacitor. The sum of the power supplied by both sources at each instant of time is virtually equal to the power demand, as necessary to keep the output voltage stable. As the system acts as a low pass filter for the battery current, the RMS current on battery is reduced (in comparison with a system with battery only), and higher efficiency on storage is expected. Also, lower discharge rates and attenuation of high frequency components in battery current should result in longer battery life.
Figure 8: Experimental waveforms
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APPENDIX I Derivation of (2), based on control diagram of Fig. 3, with ) removed. the ultracapacitor voltage controller ( When convenient, the DC level was removed. As the system is supposed to be linear and stable, this does not change the frequency response.
APPENDIX II Derivation of ultracapacitor current over load current transfer function, based on control diagram of Fig 3.
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APPENDIX III Derivation of battery current over load current transfer function, based on control diagram of Fig 3.
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ACKNOWLEDGMENT The authors thank to Ariadne Maria Brito Rizzoni Carvalho, Edson Adriano Vendrusculo, Fábio Benjovengo, and José Claudio Geromel for the revision of original manuscript and useful suggestions.
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