Capacity Design of Supercapacitor Battery Hybrid Energy Storage System with Repetitive Charging via Wireless Power Transfer

Capacity Design of Supercapacitor Battery Hybrid Energy Storage System with Repetitive Charging via Wireless Power Transfer Toshiyuki Hiramatsu Department of Electric Engineering The University of Tokyo Kashiwanoha, Kashiwa, Chiba, Japan Email: hiramatsu@hflab.k.u-tokyo.ac.jp Xiaoliang Huang Graduate School of Frontier Science The University of Tokyo Kashiwanoha, Kashiwa, Chiba, Japan Email: huang@hflab.k.u-tokyo.ac.jp Yoichi Hori Graduate School of Frontier Science The University of Tokyo Kashiwanoha, Kashiwa, Chiba, Japan Email: hori@k.u-tokyo.ac.jp Abstract The widely used energy storage system for electric vehicle and electric operating machine based on battery has critical disadvantages. A solution for this problem is the use of battery/supercapacitor (SC) hybrid energy storage system (HESS) due to advantages of SC in high power density, high cycle capability, and long life time. However, energy density of electric energy storage is much lower than the one of combustion engine. A solution for these problem is the repetitive charge for HESS via Wireless Power Transfer (WPT). In order to improve the transmission efficiency, the method of using a DC-DC converter to control secondary input impedance has been proposed in previous research. In this paper, a framework of HESS with WPT charging system is proposed for vehicle and electric operating machine application. Furthermore, capacity of HESS with WPT repetitive charging is designed, based on the requirements of the application. Index Terms Supercapacitor, Battery, Hybrid Energy Storage System, Repetitive Charging, Wireless Power Transfer, Capacity Design. I. INTRODUCTION Energy storage system is a key point in electric vehicles (EV) and electric operational machines. One of the most commonly used energy storage devices is battery. However, battery has three critical disadvantages. The first one is that charging/discharging speed is slow due to battery stores energy with chemical reactions.the second one is that battery energy density is lower than that of combustion engine. The third one is that the lifetime is short because battery is damaged by charge and discharge. A common solution of these problems is to equip huge batteries on board but such battery is expensive and heavy []. In order to solve these problems, battery/supercapacitor (SC) Hybrid Energy Storage System (HESS) has been proposed [2], [3]. SC as energy storage device has been widely used because SC has high power density, high cycling capability, and long life time [4] [6]. Due to these advantages of SC, for EV application, HESS can achieve high acceleration performance, high efficiency of regenerative brake, extension of battery life, and low cost. However, energy capacity of HESS is limited for longdistance cruising. In order to improve the cruising range of Fig.. The scheme of system applied WPT to HESS. EV and electric operational machine, HESS must be charged repetitively. The plug-in charge brings some problems and it can be an obstacle for automatic operation [7]. WPT via magnetic resonant coupling is suitable to repetitive charge [8] [0]. This method, introduced in 7, allows high transmission efficiency over relatively larger gap, compared to induction method. For high transmission efficiency, controlling load impedance with DC-DC converter is proposed []. When the designing actual system, it is necessary to design the capacity of system as well. Previous researchers proposed a capacity design of HESS, however they did not consider repetitive charging [2], [3]. In this paper, a framework of HESS with WPT charging system is proposed for vehicle and electric operating machine application and the capacity of HESS with WPT repetitive charging is designed, based on the requirements of the application. II. HESS WITH WPT CHARGING SYSTEM Fig. shows the WPT system applied to HESS. In this research, this topology is considered. In this topology, DClink voltage is fixed as battery voltage because battery is connected directly to DC-link. Transmission power from WPT is absorbed by battery and SC or consumed by motor. The

Fig. 2. Image of electric operating machine and operation pattern. TABLE I DEFINITION OF THE PARAMETERS FOR HESS. E D (Wh) E 0 (Wh) E chref (Wh) P D (W) α p Bdis (W/kg) p Bch (W/kg) e Bat (Wh/kg) E Bat (Wh/kg) P Bdis (W/kg) P Bch (W/kg) p SC (W/kg) e SC (Wh/kg) P SC (W) E SC (Wh) P dis (W) P charge (W) E charge (Wh) n P W P T (W) M T charge (h) Total energy for operation Initial energy of HESS Demanded Energy per one charge Maximum power Weight ratio of SC Discharge power density of battery Charge power density of battery Energy density of battery Energy of battery Discharge power of battery Charge power of battery Power density of SC Energy density of SC Power of SC Energy of SC Discharge power of HESS Charge power of HESS Charge energy of HESS The number of charge Charge degree Charge power from WPT Weight of HESS The total of the charge time purpose of the DC-DC converter connected to SC is to control power flow between battery and SC, and the DC- DC converter connected with coil is employed to control transmission efficiency and transmission power. III. CAPACITY DESIGN OF HESS AND WPT In this section, capacity design of HESS and WPT based on requirements specification of application is proposed. The configuration of electric operating machine and operation pattern is showed in Fig. 2. TABLE. I shows the parameters for capacity design of HESS. The operating machine has Hybrid storage and coil to charge power from WPT. The operating machine works from starting point to goal point. The electric operating machine is repetitively charged after it stops by the charge point. The SC is fully charged at that point and completely discharged before reaching next point. In this paper, the losses in DC-DC converter and HESS and energies for moving the machine to the next charge point are not considered. Fig. 3. Energy variation of HESS. A. Different constraints for capacity of HESS ) Charge degree of battery: When HESS is charged repetitively by WPT, the SC is assumed to be fully charged in each charge point. Only charge degree of battery varies from 0.0 to.0, where =.0 indicates that battery is fully charged. In other words, can be defined as the variation of SOC of battery. Capacity of HESS is designed by as one variable value. 2) Constraint from demanded energy: The variation of energy of HESS is shown in Fig. 3. Assuming that HESS is charged with the same amount of energy in each charge point, E chref is given as E chref = E D E 0. () n Assuming that the initial SOC of HESS is %, E 0 is given as E 0 = {( α)e Bat + αe SC }M HESS. (2) E ch is obtained as E ch = {( α)e Bat + αe SC }M HESS. (3) In order to complete operation, operating machine has to be charged with energy higher than E chref. The constraint from demanded energy is calculated from the condition E chref E ch and Eq. () (3) E D n{( α)e Bat ( + n ) + ( + n )αe SC} M HESS. 3) Constraint from demanded power: The total power of the battery and SC, P dis is given as (4) P dis = {( α)p Bdis + αp SC }M HESS. (5) The constraint from demanded power is calculated from P D P dis P D ( α)p Bdis + αp SC M HESS. (6)

TABLE II REUIREMENT SPECIFICATIONS AND ENERGY STORAGE DEVICES PARAMETERS. E D P D e Bat e SC p Bdis p Bch p SC P W P T 00 Wh 00 W 80 Wh/kg 3.6 Wh/kg 0 W/kg W/kg 0 W/kg 00 W 4) Constraint from charge power: When the operating machine is charged, the equipment of WPT is optimized by using maximum power. In addition, the SC and battery are charged with constant power. The received power from WPT is used to simultaneously charge both SC and battery. Using this assumption, charge time can be minimized. Charge power P charge = P W P T should be divided by the ratio of the energies to satisfy this assumption. Therefore, the distribution ratio of the charge power of SC and battery is given as P Bch : P SC = ( α)e Bat : αe SC. (7) The charge power of battery and SC are respectively P Bch = ( α)m HESS p Bch (8) P SC = αm HESS p SC. (9) It is necessary to satisfy charge constraints of battery and SC to distribute charge power by the energy ratio : such constraints are obtained from Eq. (7) (9) as e Bat p Bch {( α)e Bat + αe SC } P charge M HESS (0) 0 0 3 2.5 2.5 (a) Constraint of energy. 0 0 (c) Constraint of SC charge power. 0 0 0 (b) Constraint of power. 0 Fig. 4. The case of =.0. 0 0 (d) Constraint of battery charge power. 0 Fig. 5. HESS weight in the case of =.0. e SC p SC {( α)e Bat + αe SC } P charge M HESS. () In the case of being satisfied, T charge is T charge = E D {( α)e Bat + αe SC }M HESS P W P T. (2) The operating machine has to have HESS which satisfies Eq. (4), (6), (0), () in order to complete operation. IV. CALCULATION RESULTS OF HESS CAPACITY DESIGN The parameters of operating machine are shown in Table. II. A. Case of fixed In the case of =.0, 0.0, 0., M HESS and the weight of battery are calculated by the change of α. The cases of, 2, 3, 5, 0,, is considered. ) Case of =.0: Fig. 4 shows calculation results of four constraints of Eq. (4), (6), (0), () by the change of α in the case of =.0. From Fig. 4 (b), (c), (d), these constraints draw the same curves in all n because they are not affected by n. From Fig. 4 (c), the constraint of SC charge power is much smaller than other constraints Fig. 5 shows M HESS is calculated from Fig. 4. From Fig. 4, 5, when α is less than 0.27, M HESS is decided by Eq. (6). M HESS can be decreased as α increases because power density of SC is larger than the one of the battery. When α is larger than 0.27, M HESS is decided by Eq. (0) because the battery should have large charge power to completely charge in each charge point. M HESS should be large as α increases because battery has to satisfy Eq. (0) From this result, in the case of =.0, M HESS can be minimized when Eq. (6), (0) are satisfied. The same curves are drawn in all the number of charge times because Eq. (6), (0) are not affected by the n.

0 0 0 0 0 0 0 (a) Constraint of demanded energy. 0 0 (c) Constraint of SC charge power. 0 (b) Constraint of demanded power. Fig. 6. The case of = 0.0. 0 0 (d) Constraint of battery charge power. 0 3 2.5 2.5 (a) Constraint of energy. 0 0 (c) Constraint of SC charge power. Fig. 8. The case of = 0.. 0 0 (b) Constraint of power. 0 0 (d) Constraint of battery charge power. 0 0 0 Fig. 7. HESS weight in the case of = 0.0. 0 Fig. 9. HESS weight in the case of = 0.. 2) Case of = 0.0: Fig. 6 shows calculation results of four constraints of Eq. (4), (6), (0), () by the change of α in the case of = 0.0. From Fig. 6 (b), (c), (d), these constraints draw same curves in all n because they are not affected by n. Fig. 6 (d) shows the constraint of battery charge power is 0 because battery is not charged in the case = 0.0. Fig. 7 shows that M HESS is calculated from Fig. 6. In the range which M HESS decreases by increasing α, M HESS is decided by Eq. (). The SC should absorb all charged power. The M HESS can be decreased as α increases. In the range which M HESS increases by increasing α, M HESS is decided by Eq. (4) because energy density of HESS is decreased as α increases. If n is frequent, M HESS can be small because HESS does not need large capacity of energy. From this result, in the case of = 0.0, if number of charge n is frequent, only SC should be used for energy storage. If n is less, there is a α value that minimizes M HESS. 3) Case of = 0.: Fig. 8 shows calculation results of four constraints of Eq. (4), (6), (0), () by the change of α in the case of = 0.. From Fig. 8 (b), (c), (d), these constraints draw same curves in all n because they are not affected by n. Fig. 9 shows that M HESS shows that M HESS is calculated from Fig. 8. When M HESS decreases by increasing α, M HESS is decided by Eq. (6). In the case which α is large and n is frequent, M HESS is decided by Eq. (0). In the case where α is large and n is less, M HESS is decided by Eq. (4). These results indicate that in the case where several n and has an optimal α that minimizes M HESS. B. Optimal capacity ratio of HESS Fig. 0 shows the calculation result of M HESS by the change of. In this case, α is selected to minimize M HESS in each. From Fig. 0, M HESS is minimized in a certain. Furthermore, the more charge points there are, the smaller is that minimize M HESS. This result indicates that when

55 55 25 25 Fig. 0. HESS weight in the case of changing 3.0 kw. Fig.. HESS weight in the case of changing.5 kw. n increases, the battery charge energy in each charge point can be small. Therefore, if n is frequent, only SC should be equipped as an energy storage system. The condition to minimize M HESS is that Eq. (4), (6), (0) should be the same. In this case, Eq. () is not considered because Eq. () affects only to decide minimum M HESS when is very small due to high power density. From Fig. 0, if M HESS is charged many times, M HESS can be small. However, the number of charge times is related to the number of charge points. If the number of charge points is not enough, operating machine should move to charge points. In brief, the number of charge times is limited. C. Effect of Charge Power Fig., 2 shows the result of calculation of M HESS in the case of P W P T =.5 kw, 4.5kW. The minimum M HESS increases as P W P T becomes larger. Since M HESS should be large to satisfy Eq. (0). From this result, the minimum M HESS can be small if P W P T is small. However, if P W P T is small, T charge should be extended. Therefore, P W P T should be chosen in consideration of T charge. In addition, the optimal becomes smaller as P W P T becomes larger. This indicates that SC is suitable to charge huge power. D. Capacity design guidance of HESS As above the minimum M HESS is obtained when E D n{( α)e Bat ( + n ) + ( + n )αe SC} = M HESS. (3) P D ( α)p Bdis + αp SC = M HESS. (4) e Bat p Bch {( α)e Bat + αe SC } P W P T = M HESS. (5) are satisfied. If P W P T is decided, variable parameters are M HESS, n,, α. Therefore, the minimum M HESS can be calculated by giving one variable parameter. From these results, 55 25 Fig. 2. HESS weight in the case of changing 4.5 kw. the minimum M HESS and T charge can be calculated in each P W P T shown as Fig. 3, 4. From Fig. 3, 4, M HESS can decrease more when P W P T is low. However, T charge becomes longer. From these results, it is possible to design the optimal HESS according to requirements. In addition, it is assumed that electric operating machine charges after it stops in this case. However, this algorithm can be applied to EV with charging during running. V. CONCLUSION AND FUTURE WORK A framework of HESS with WPT charging system is proposed for vehicle and electric operating machine application. HESS can realize desired characteristic energy storage and WPT can supply energy to HESS repetitively. This system can decrease energy storage on board. The capacity design guidance of HESS with repetitive charging via WPT is proposed. Charge degree of battery is defined and α to minimize M HESS exists in several. In addition, it is indicated that that minimizes M HESS and conditional equation. If the number of charge times n is large enough,

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