Implementation of standalone dynamic solar array fed permanent magnet synchronous motor drive using zero voltage switching resonant converter for the reduction of switching losses and oscillations

2.1. Conventional circuit diagram

The conventional circuit diagram is shown in Fig. 2. The researcher has proposed the parametric value of ($C_0$ and $C_1$) of 24 V, 70 W solar PV module for the system and the same is modeled using the five parameter model [27]. The boost derived single inductor based dual input/output DC-DC converter (SI-DIO) used in the proposed power flow management system is shown in Fig. 2. It consists of diode Din which interfaces the solar PV module to the converter and also prevents reverse power flow to the solar PV module. The capacitor $C$ in is connected in parallel to the solar PV module to reduce the solar PV voltage ripples. The switches $S_2$ and diode $D_2$ is used to set the battery as an output to store excess solar PV power. The switch $S_3$ is used to set the battery as an input to supply power to the standalone DC load. The capacitor Co is connected across the output to reduce the output voltage ripples. The converter has two modes of operation namely dual output boost mode (DOBM) when the power from solar PV module exceeds DC load demand and dual input boost mode (DIBM) when there is a deficit. The circuit configuration for both the modes is shown in Fig. 2 [27].

Fig. 2Conventional schematic circuit diagram [27]

During DOBM, the solar PV module acts as a power source feeding the battery through the switch $S_2$ and the DC load through the diode $D_1$. The single inductor based dual IO removed (input/output) DC-DC converter has three states as shown in Fig. 2. In the first state, the inductor is charged by power from the solar PV module through switch $S_{boost}$. In the second state, switch $S_{boost}$ is turned off and the inductor discharges to the DC load through the diode $D_1$. In the third state, the surplus power is discharged to the battery by turning on the switch $S_2$. Since, the required voltage of the standalone DC load is higher than that of the battery, the diode $D_1$ is reverse biased and the standalone DC load is cut off. Typical waveforms for the inductor current $I_L$, the inductor voltage $v_l$, the battery current $i_{bat}$ and the output DC load voltage $v_o$ for this mode is shown in Fig. 2 [27].

Wu Deng proposed [28], an improved ant colony optimization (ICMPACO) algorithm based on the multi-population strategy, co-evolution mechanism, pheromone updating strategy, and pheromone diffusion mechanism is proposed to balance the convergence speed and solution diversity, and improve the optimization performance in solving the large-scale optimization problem. In the proposed ICMPACO algorithm, the optimization problem is divided into several sub-problems and the ants in the population are divided into elite ants and common ants in order to improve the convergence rate, and avoid to fall into the local optimum value. The pheromone updating strategy is used to improve optimization ability.

Wu Deng proposed [29] the improved PSO algorithm is used to optimize the parameters of least squares support vector machines (LS-SVM) in order to construct an optimal LS-SVM classifier, which is used to classify the fault. Finally, the proposed fault diagnosis method is fully evaluated by experiments and comparative studies for motor bearing for reduction of vibration.

Another algorithm MGACACO by Wu Deng [30] proposed makes use of the exploration capability of GA and stochastic capability of ACO algorithm. In the proposed MGACACO algorithm, the multi-population strategy is used to realize the information exchange and cooperation among the various populations. The chaotic optimization method is used to overcome long search time, avoid falling into the local extremum and improve the search accuracy.

Huimin Zhao, Wu Deng [31] proposed the EEMD method which is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs) with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM) model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM) for fulfilling fault pattern recognition.

Wu Deng [32] proposed Another approach, the Alpha-stable distribution theory is used to replace the uniform distribution in order to escape from the local minima in a certain probability and improve the global search ability. Next, the DOADAPO algorithm is used to solve the constructed multi-objective optimization model of gate assignment in order to fast and effectively assign the gates to different flights in different time.

Huimin Zhao, Wu Deng [33] proposed damage degree identification method based on high-order difference mathematical morphology gradient spectrum entropy (HMGSEDI) is proposed in this paper to solve the problem that fault signal of rolling bearings are weak and difficult to be quantitatively measured. In the HMGSEDI method, on the basis of mathematical morphology gradient spectrum and spectrum entropy, the changing scale influence of structure elements to damage degree identification is thoroughly analyzed to determine its optimal scale range. The high-order difference mathematical morphology gradient spectrum entropy is then defined in order to quantitatively describe the fault damage degree of bearing. The discrimination concept of fault damage degree is defined to quantitatively describe the difference between the high-order differential mathematical entropy and the general mathematical morphology entropy in order to propose a fault damage degree identification method.

From various literature and analysis from the conventional system switching losses across the switch $S_1$ is high which makes the system with reduced efficiency and the dynamic solar array varies, to overcome this DISOZVS converter is proposed.

2.2. Battery management system for solar energy storage

While partial shading occurs in the PV array, battery within the shape of strength storage device and a bidirectional DISOZVS converter are used to meet the call for strength. Among the various configurations of PV era, a stand-by myself PV-battery powered backup machine will be applied in diverse kinds of applications. A chargeable battery is generally exploited inside the device for electricity saving while the solar electricity generated exceeds the energy wished via the weight. On this the auxillary switch ($S_2$) is in an active part. The electricity stored can be useful in maintaining the gadget operation at the same time as the shading to the PV panel is executed. Hence the boost switch ($S_3$) is also in an energetic element. Two Power switches ($S_2$ and $S_3$) used in the converter structure act as the leader controllable factors controlling the strength waft of the converter. The proposed schematic DISOZVS converter are shown in Fig. 3.

2.3. Proposed DISOZVS converter

Interval 1 ($t_0-t_1$): at time $t_0$, the lower switch $Q_2$ is turned ON and the upper switch $Q_1$ is turned OFF with diode $D_1$, $D_2$ reverse biased as shown in Fig. 3. During this time interval the converter operates in boost mode and the inductor is charged and current through the inductor increases.[26]

Interval 2 ($t_1-t_2$): during this interval both switches $Q_1$ and $Q_2$ is turned OFF. The body diode $D_1$ of upper switch $Q_1$ starts conducting as shown in Fig. 3. The converter output voltage is applied across the motor. As this converter operates in boost mode is capable of increasing the battery voltage to run the motor in forward direction.

Interval 3 ($t_2-t_3$): at time $t_3$, the upper switch $Q_1$ is turned ON and the lower switch $Q_2$ is turned OFF with diode $D_1$, $D_2$ reverse biased as shown in Fig. 3. During this time interval the converter operates in buck mode.

Interval 4 ($t_3-t_4$): during this interval both switches $Q_1$ and $Q_2$ is turned OFF. The body diode $D_2$ of lower switch $Q_2$ starts conducting as shown in Fig. 3.

Fig. 3Proposed circuit diagram of DISOZVS converter

2.3.1. Case 1: DISOZVS Converter modes of operation

Mode A. In mode A, at the instant of time $t_0$ the solar PV source delivers the power to the inductor $L_1$ which is connected in series with the Solar PV source, so that the inductor $L_1$ gets charged and the energy is stored in the inductor $L_1$ at the dual output Boost Converter are shown in Fig. 4 and its dynamic equation are illustrated in Eqs. (1-2):

1

$L_1\frac{d{i}_{L1}}{dt}=-V_{C0},$

2

$C_0\frac{d{V}_0}{dt}=-\frac{V_0}{R_L}.$

Fig. 4Mode A solar power charges inductor L1

Mode B. In mode B, the resonant switch $S_r$ gets turned ON. At this instant of time $t_1$ the resonant inductor $L_r$ which is connected in series with the inductor $L_1$ and the Solar PV module, gets charged and stores energy when the inductor $L_1$ discharges. Meanwhile the inductors $L_1$ is again charged by the PV source and the energy is stored in the inductor $L_1$. In this mode both the inductors $L_1$ and $L_r$ gets charged and stores energy as shown in Fig. 5 and its dynamic equation are illustrated in Eq. (3):

3

$C_0\frac{d{V}_0}{dt}=\frac{V_{C0}+V_{in}-V_0}{R_L}.$

Fig. 5Mode B solar power charges inductor L1 and Lr

Mode C. In mode C, at the instant $t_2$ the potentials at inductor $L_1$ and resonant inductor $L_r$ is equal. Now the energy stored in both the inductor $L_1$ and the resonant inductor $L_r$ are discharged to charge the resonant capacitor $C_r$ which is connected in series with the resonant inductor $L_r$ and the energy gets stored in the capacitor $C_r$ as shown in Fig. 6 and its dynamic equation are illustrated in Eq. (4):

4

$C_0\frac{d{V}_0}{dt}=i_{L1}-\frac{V_0}{R_L}.$

Fig. 6Mode C inductor L1 and Lr discharges to charge capacitor Cr

Mode D. In mode D, the auxiliary switch $S_1$ is turned on at the instant of time $t_3$, the resonant capacitor $C_r$ gets discharged to attain zero potential at node A. The capacitor $C_0$ gets charged by the resonant capacitor $C_r$. The capacitor $C_0$ is connected in parallel with the resonant inductor $L_r$ and resonant capacitor $C_r$. The capacitor $C_0$ stores energy by the resonant capacitor $C_r$. as shown in Fig. 7.

Fig. 7Mode D capacitor Cr discharges to charge capacitor Co

Mode E. In mode E, the auxiliary switch $S_1$ is turned ON, the capacitor $C_0$ which is connected in parallel with the resistive load RL. At the instant of time t₄, the energy stored in the capacitor $C_0$ is discharged to run the resistive load. In this mode, the power from the Solar PV module is sufficient to the resistive load RL as shown in Fig. 8 and its dynamic equation are illustrated in Eq. (5):

5

$C_0\frac{d{V}_0}{dt}=i_{Lr}-\frac{V_r}{R_L}.$

Fig. 8Mode E capacitor Co discharging mode

2.4. Control strategy of DISOZVS

The voltage follower is required for controlling of DISOZVS converter operating at discontinuous conduction mode. For regulating the total output voltage $C_0$ of DISOZVS converter measurement sensors are required. Fig. 9 shows the closed loop control of DISOZVS converter. This control strategy comprises a voltage error generator, Output Voltage Controller (OVC), Capacitor Voltage Controller (CVC) and a PWM generator. The output voltage $C_0$ is generated by using the error generator comparison voltage are given in Eqs. (6-7):

where, $V_{ce1}$ – error control voltage, $V_T^{*}\left(k\right)$ – error output voltage, $V_T\left(k\right)$ – total output voltage, $K_p$, $K_i$ – proportionality constant.

The $k_p=$0.2, $k_i=$0.1 are used for error control strategy which is given in Eq. (8):

Fig. 9Control strategy of DISOZVS

2.5. Analysis of power losses on DISOZVS

2.5.1. Resonant Switch conduction losses

During analysis of $S_r$ conduction, the $R_{ds}$ is on at junction temperature and it is illustrated in the Eqs. (9-11). The delta value of inductor, capacitor are calculated and given in Eqs. (12-13):

9

$P_{cond-Sr}=I_{Sr}^2\times R_{DS-on},$

10

$I_{SrLr}^2=d_1\times \left[I_{OLr}^2+\frac{∆I_{OLr}^2}{12}\right],$

11

$I_{SrCr}^2=d_{12}\times \left[I_{OC1}^2+\frac{∆I_{OCr}^2}{12}\right],$

12

$∆I_{OLr}=\frac{I_{OLr-max}-I_{OLr-min}}{2}=\frac{5.7-0}{2}=2.85,$

13

$∆I_{OCr}=\frac{I_{OCr-max}-I_{OCr-min}}{2}=\frac{4.5-0}{2}=2.25.$

The conduction of inductor, capacitor, switching currents of DISOZVS are shown in Fig. 10.

Fig. 10a) Conduction of inductor, capacitor, switching currents of DISOZVS, b) key waveforms of various parameters

a)

b)

The effectiveness of framework is indirect to the complete power. All output power, in the DISOZVS converter, such as conduction, exchanging, diode and inductor are indirect. Event of the conduction misfortunes is because of the declining voltage over the power semiconductor device just as the present move through the power semiconductor device striking in theme. Exchanging misfortunes are supported by the simultaneous event of voltage and current on the power semiconductor device while exchanging. The key waveforms of DISOZVS converter are appeared in Fig. 10(b). $I_{in}$, $i{L}_1$, $i{D}_1$, $i{D}_2$, and $i{C}_1$ are the current through the information supply, inductor $L_1$, diodes $D_1$ and capacitor $C_0$ respectively. Evaluation of these misfortunes should be possible utilizing disentangled gadget models:

14

$P_{Turn-Sr}=\frac{1}{2}\left(t_r+t_f\right)\times I_{Sr}^2\times V_{D-Sr}\times F_{sw},$

15

$P_{Turn-S1}=0.009\mathrm{W},$

where $t_r$ is rise time, $t_f$ is fall time, $I_{Sr}^2$ refers to$$current conduction of resonant switch ($S_r$) (refer Eq. (14)), $V_{D-Sr}$ stands for drain voltage of switch ($S_r$) and $F_{sw}$ is operating switching frequency (5 kHz).

2.6. Implementation of dynamic standalone solar array, battery power, four switch inverter fed PMSM drive

2.6.1. Case 2: battery charging mode

2.6.1.1. Mode F battery charging mode at ${\mathit{R}}_{\mathit{L}}$

In mode F as shown in Fig. 11 the power generated at the solar PV module is excess for running the resistive load RL. Such that, the excess power from the PV source is used to charge the battery which is used as a backup source. At the instant the auxiliary switch $S_2$ is turned ON. The excess power from the solar PV source is used to charge the battery through the auxiliary switch $S_2$.

Fig. 11Mode F solar power to RL load with charging battery

2.6.1.2. Mode (${\mathit{F}}_1$) battery charging mode at PMSM

In mode $F_1$ as shown in Fig. 12 the power generated at the solar PV module is excess for running the PMSM motor with regulated voltage. Such that, the excess power from the PV source is used to charge the battery which is used as a backup source. At the instant the auxiliary switch $S_1$ is turned ON. The excess power from the solar PV source is used to charge the battery through the auxiliary switch $S_2$.

Fig. 12Mode F1 solar power to motor load with charging battery

2.6.2. Case 3: mode G battery discharging mode at ${\mathit{R}}_{\mathit{L}}$

In mode G as shown in Fig. 13 the power from the solar PV source is insufficient to run the resistive load RL, such that the auxiliary switch $S_3$ is turned ON to draw power from the battery to run the resistive load RL and the auxiliary switch $S_1$ is also turned ON. At this instant, the power from the battery is used to charge the inductor $L_1$ and the inductor $L_1$ stores the energy from the battery.

Fig. 13Mode G solar power to RL with discharging battery

2.6.2.1. Mode ${\mathit{G}}_1$ battery discharging mode at PMSM

In mode $G_1$ as shown in Fig. 14 the power from the solar PV source is insufficient to run the motor, such that the auxiliary switch $S_3$ is turned ON to draw power from the battery to run the load and the auxiliary switch $S_1$ is also turned ON. At this instant, the power from the battery is used to charge the inductor $L_1$ and the inductor $L_1$ stores the energy from the battery.

Fig. 14Mode G1 solar power to motor load with discharging battery

2.6.3. Case 4: mode H battery in ideal condition at ${\mathit{R}}_{\mathit{L}}$

In mode H as shown in Fig. 15 the stored energy in the inductor $L_1$ is discharged through the diode $D_0$ which is forward biased and charges the capacitor $C_0$. The capacitor $C_0$ is charged by both the solar PV source and the battery. The capacitor $C_0$ stores the energy and it discharges to run the resistive load RL. Thus, resistive load RL is run by the power from the solar PV source and the power drawn from the battery at the dual output boost mode.

Fig. 15Mode G Solar power to RL with ideal battery

2.6.3.1. Mode ${\mathit{H}}_1$ battery in ideal condition at PMSM

In mode $H_1$ as shown in Fig. 16 the stored energy in the inductor $L_1$ is discharged through the diode $D_0$ which is forward biased and charges the capacitor $C_0$. The capacitor $C_0$ is charged by both the solar PV source and the battery. The capacitor $C_0$ stores the energy and it discharges to run the motor. Thus, load is run by the power from the solar PV source and the power drawn from the battery at the dual output boost mode.

Fig. 16Mode G1 solar power to RL with ideal battery

3.1. Simulations results and discussions

To find out the performance of the proposed converter under the present control strategy, MATLAB simulations in different conditions have been performed. The simulation parameters such as input voltage ($V_{in}$), input current ($I_{in}$), input power ($P_{in}$),output voltage, current and power of DC-DC converter ($V_O$, $I_O$ and $P_O$) respectively, motor results such as speed, torque and stator current are used to evaluate the performance of the proposed system. The Simulation specifications of the proposed system are shown in Table 1.

3.1.3. Solar PV input power (${\mathit{P}}_{\mathit{i}\mathit{n}}$)

Fig. 17(c) determines the PV input power of the proposed system. From the input waveform of the DISOZVS it is referred that the power is about 29.25 W which changes according to the solar irradiation at 0.2 sec.

Fig. 17Solar PV DISOZVS input: a) voltage, b) current, c) power

a)

b)

c)

3.2. Proposed simulation output for battery

3.2.2. Battery charging and disharging current

Fig. 19 determines the Battery current of the proposed system. The waveform describes the charging current is –0.4 A and discharging current is 0.6 A in the battery according to the load power requirements.

Fig. 18Solar PV battery output voltage

Fig. 19Solar PV power demand battery charging and discharging current

3.2.3. Battery charging and discharging power

Fig. 20 determines the battery power of the proposed system. The waveform describes the charging power is 17.5 W and discharging power is 14 W in the battery according to the load power requirements.

Fig. 20Solar PV power demand battery charging and discharging power

3.2.4. Battery state of charge

Fig. 21 determines the state of charging in Battery of the proposed system. The waveform describes the ideal, charging and discharging state in the battery.

Fig. 21Battery charging and discharging state of charge (SOC%)

3.3. Proposed simulation output for converter

3.3.3. Solar PV output power (${\mathit{P}}_{\mathit{o}}$)

Fig. 22(c) determines the DC power of the proposed system. The waveform represents the output DC power which is about 15 W in accordance with the PV source and the battery source which is used to run the load.

Fig. 22Solar PV DISOZVS output: a) voltage, b) current, c) power

a)

b)

c)

3.4. Proposed simulation output for motor parameters

3.4.3. Direct current (${\mathit{I}}_{\mathit{d}}$), quadrature current (${\mathit{I}}_{\mathit{q}}$)

Fig. 23(c) determines the direct and quadrature current of the proposed system. The waveform describes the direct current (2.2 A) and quadrature current (–4 A) obtained in the PMSM drive which is operated by the converter output.

Fig. 23DISOZVS motor: a) speed, b) torque, c) Id, Iq

a)

b)

c)

3.4.4. Three phase motor current

Fig. 24 determines the motor three phase current of the proposed system. The waveform represents the Three phase current which is required to operate the PMSM drive.

Fig. 24DISOZVS motor stator three phase current

3.5. Comparison of simulation output of switching losses s₁in percentage

Fig. 25 determines the switching losses in proposed system. From the waveform it is referred that the switching losses is reduced to 5 % when compared with the conventional system.

3.6. Experimental analysis of DISOZVS and B4-inverter fed PMSM drive

The experimental verification is conducted for validating the proposed DISOZVS and B4-Inverter fed PMSM drive. The hardware of DISOZVS and B4-Inverter fed PMSM drive is presented in Fig. 26.

Fig. 25Comparison of conventional and proposed switching loss across S1

a)

b)

Fig. 26Experimental illustration for DISOZVS B4-inverter fed PMSM

The hardware DISOZVS and B4-Inverter fed PMSM drive consists of 16-Bit digital signal Peripheral Interface Controller (PIC16F877) for DISOZVS control, B4-Inverter control, gate driver circuit for DISOZVS and B4-Inverter MOSFET’s. The feedback signals are processed with the help of measurement devices and circuit, and thereafter the control signals to the DISOZVS and B4-Inverter are transmitted by a PIC16F877 microcontroller. The DISOZVS converter is coupled among PV, Battery and load ports. A 36 W PMSM drive is powered by a B4-Inverter in the form of a load port of the new system. The DISOZVS converter input power is changed from 12 W to 60 W which in turn, is utilized for exemplifying the performance of the proposed system the experimental block diagram is shown in Fig. 26. Table 2 shows the experimental specifications.

Fig. 27 determines the Switching pulses of Battery charging mode ($S_1$, $S_2$). Here, the voltage level is equal to 15 V across the boost switch S₁ and Battery charging switch $S_2$.

Fig. 28 determines the Switching pulses of Battery charging mode ($S_1$, $S_3$). Here, the voltage level is equal to 15 V across the boost switch S1 and –5 V across the Battery discharging switch $S_3$.

Fig. 27Switching pulses of battery charging mode (S1, S2)

Fig. 28Switching pulses of battery charging mode (S1, S3)

3.6.3. Switching pulses of inverter (${\mathit{S}}_5$,${\mathit{}\mathit{S}}_7$)

Fig. 31 determines the Switching pulses of inverter ($S_5$, $S_7$). Here, the voltage level is equal to 15 V across inverter switch $S_5$ and inverter switch $S_7$.

Fig. 29Switching pulses of battery charging mode (S1, Sa)

Fig. 30Switching pulses of inverter (S5, S6)

Fig. 31Switching pulses of inverter (S5, S7)

3.6.5. Switching pulses of battery discharging mode (${\mathit{S}}_1$, ${\mathit{S}}_2$)

Fig. 33 determines the Switching pulses of battery discharging mode ($S_1$, $S_2$). Here, the voltage level is equal to 15 V across boost switch $S_1$ and –5 V across the battery charging switch $S_2$.

Fig. 32Switching pulses of inverter (S5, S8)

Fig. 33Switching pulses of battery charging mode (S1, S2)

3.6.6. Switching pulses of battery discharging mode (${\mathit{S}}_1$,$\mathit{}{\mathit{S}}_{\mathit{a}}$)

Fig. 34 determines the Switching pulses of battery discharging mode ($S_1$, $S_a$). Here, the voltage level is equal to 15 V across boost switch $S_1$ and auxiliary switch $S_a$.

Fig. 34Switching pulses of battery discharging mode (S1, Sa)

3.6.10. Battery charging current

Fig. 38 determines the output waveform of battery charging current. Here, the current level in the battery is equal to –0.5 A at charging mode.

Fig. 35Switching pulses of battery discharging mode (S1, S3)

Fig. 36Battery charging voltage when excess power from source

Fig. 37Battery discharging voltage when load power demands

Fig. 38Battery charging current when excess power from source

3.6.11. Battery discharging current

Fig. 39 determines the output waveform of battery discharging current. Here, the current level in the battery is equal to 6 A at discharging mode of operation. Fig. 40 shows the comparison of switches, switching losses of proposed DISOZVS with conventional converter. Fig. 41 curve represents the comparison of proposed DISOZVS with conventional converter switching Losses, switching frequency, efficiency. Comparison of conventional and proposed converter for various objects are shown in Table 3 which shows the proposed converter is more efficient. Table 4 shows the conduction of switches of proposed converter.

Fig. 39Battery discharging current when load power demands

Table 3Comparison of conventional and proposed converter

S. No	Objects	Conventional converter 1 (Anand et al. 2018) [27]	Conventional converter 2 (Sathish Kumar et al. 2017, 2018) [18]	Proposed converter (DISO-DISOZVS)
1	No of switches	3	3	4
2	Efficiency	92.1	91.4	93.79
3	Switching losses in %	35 %	40 %	5 %
4	Conversion topology	Boost	Buck-Boost	Buck-Boost
5	Switching frequency	10 kHz	20 kHz	10 kHz

Table 4Conduction of switches for proposed converter

Modes	Switch $S_1$	Switch $S_2$	Switch $S_2$	Switch $S_r$	Capacitor $C_o$
a	0	0	0	0	Off
b	0	0	0	1	On
c	0	0	0	0	ON
d	1	0	0	0	ON
e	1	0	0	0	Off
f	0	1	1	0	off
g	1	0	0	0	On
h	0	0	0	0	On

Fig. 40Comparison of: a) switches, b) switching losses proposed DISOZVS with conventional converter

a)

b)

Fig. 41Comparison of proposed DISOZVS with conventional converter: a) switching losses and switching frequency, b) efficiency

a)

b)

3.7. Prototype experimental test set up for proposed DISOZVS converter

A 36 W PMSM drive is powered by a solar, battery fed B4-Inverter to the load port of the new system is proposed works efficiently. The DISOZVS converter input power is changed from 12 W to 60 W which in turn, is utilized for exemplifying the performance of the proposed system experimental solar and battery power with charging, discharging, ideal compared with simulation are shown in Figs. 42-44.

Fig. 42Prototype test set up for battery ideal mode of operation to PMSM drive

Fig. 43Prototype test set up for battery charging mode of operation to PMSM drive

3.8. Performance of DISOZVS converter under step change in load condition

Fig. 45 determines the performance of DISOZVS Converter under step change in input condition using PMSM drive. At the point when load protections $R_1=R_2=$30 Ω (100 % load) is considered from 0 to 0.2 Sec. At a specific time, for example from 0.2 Sec to 0.4 Sec, load protections is all of a sudden diminished from 100 % to half ($R_1=R_2=$60 Ω) condition as appeared in Fig. 46(a). The yield voltage of the DISOZVS converter is wanted to be managed on ($V_T=$30 V). The yield voltage ($V_T$) is followed the reference esteem ($V_T^{*}$) with least relentless state blunder as appeared in Fig. 46(b).

Fig. 44Prototype type set up for battery discharging mode of operation to PMSM drive

Subsequently, the yield current ($I_T$) magnitude variation checks the proposed DISOZVS converter closed circle execution as appeared in Fig. 46(c). The time area investigation like over shoot, rise time, settling time, postponed time and steady state error, for yield voltage ($V_T$), under advance change in input/load conditions at comparison with switching frequency toe reduce noise and oscillations in pmsm is appeared on Table 5.

Fig. 45Performance of DISOZVS converter under step change in input condition using PMSM drive

Fig. 46Performance of DISOZVS converter under step change in load condition using PMSM drive

a)

b)

c)