Abstract The development of an experimental platform for photovoltaic (PV)-powered wireless charging systems of electric vehicles, with a focus on hardware design, simulation verification, and practical validation. The core controller DSP28335 is employed to manage the system’s operations. A PV model based on Simulink is established to verify the maximum power point tracking (MPPT) algorithm, while the LCC-S topology for wireless charging is analyzed using mathematical modeling and Maxwell simulations. Experimental results confirm the effectiveness of MPPT on the PV side and power transfer on the coil side, demonstrating the platform’s utility for educational and research purposes in electric vehicle technologies.
Keywords: electric vehicle; photovoltaic; wireless charging; MPPT; LCC-S topology
1. Introduction
As the demand for sustainable transportation grows, electric vehicles (EVs) have emerged as a key solution to reduce carbon emissions. Coupled with renewable energy sources, such as solar power, EVs can achieve a more environmentally friendly lifecycle. Photovoltaic (PV)-powered wireless charging systems combine the benefits of solar energy and contactless power transfer, offering convenience and efficiency for EV charging [1-3].
1.1 Research Background
Wireless charging for electric vehicles provides safety and ease of use, eliminating the need for physical connectors [4-6]. Integrating PV systems with wireless charging enhances energy sustainability, as solar energy can be directly converted and transmitted to EV batteries. Previous studies have explored various topologies and control algorithms for such systems. For example, Liao et al. [7] developed a MCWPT system capable of maintaining efficient power transfer over varying distances, suitable for EVs with different chassis heights. Zhang et al. [8] analyzed the interoperability of wireless charging systems, identifying S-type and P-type topologies as optimal for primary and secondary sides, respectively.
1.2 Objectives
The primary goal of this research is to design and validate an experimental platform that integrates PV power generation and wireless charging for electric vehicles. The platform aims to:
- Demonstrate the MPPT algorithm in PV systems.
- Analyze the power transfer characteristics of the LCC-S compensation topology.
- Provide a practical teaching tool for students to understand EV charging technologies.
2. Photovoltaic Power Generation System Design
2.1 System Structure
The PV-powered wireless charging system for electric vehicles consists of a PV panel, DC-DC converter, MPPT controller, and wireless charging modules. The block diagram in Figure 1 illustrates the energy flow: solar energy is converted to electrical power by the PV panel, regulated by the DC-DC converter, and transmitted wirelessly via coils to the EV battery [9].
2.2 Circuit Design
The PV system employs a Boost converter as the DC-DC module. Using the inductor volt-second balance principle, the relationship between input and output voltages is derived as:\(\left.\begin{array}{l} U_{i} T_{\text {on }} = T_{\text {off }} (U_{o} – U_{i}) \\ U_{o} = \frac{U_{i}}{1-D} \end{array}\right\} \quad (1)\) where \(U_{i}\) and \(U_{o}\) are input and output voltages, \(T_{\text {on}}\) and \(T_{\text {off}}\) are the on and off times of the PWM signal, and D is the duty cycle.
Under ideal conditions, the input power equals the output power, leading to:\(U_{\text {PV}} I_{\text {PV}} = U_{R} I_{R}\) where \(U_{\text {PV}}\) and \(I_{\text {PV}}\) are the PV output voltage and current, and \(U_{R}\) and \(I_{R}\) are the load voltage and current. The equivalent resistance \(R_{\text {eq}}\) of the PV system is:\(R_{\text {eq}} = (1-D)^{2} R \quad (2)\) where R is the load resistance. Adjusting the duty cycle D allows tracking the maximum power point (MPP) by modifying \(R_{\text {eq}}\).
2.3 MPPT Control Method
The perturbation and observation (P&O) method is used for MPPT. This algorithm adjusts the PV output voltage and monitors power changes:
- If the perturbed power \(P(k)\) is greater than the previous power \(P(k-1)\), continue the perturbation in the same direction.
- If not, reverse the perturbation direction.
The flowchart in Figure 2 outlines the P&O algorithm steps, where \(U(k)\) and \(I(k)\) are the current voltage and current measurements, and dU is the perturbation step [10-12].
2.4 Simulation Results
Simulations were conducted in Simulink to verify the MPPT performance under varying conditions:
- Temperature Variation: At a light intensity \(G = 1 \, \text{kW/m}^2\), the system quickly tracked the MPP when temperature increased from 25°C to 60°C (Figure 3).
- Light Intensity Variation: At \(T = 25^\circ\text{C}\), the system adapted to sudden changes in G from 1 to 1.5 \(\text{kW/m}^2\) (Figure 4).
Both results confirm the effectiveness of the P&O algorithm in tracking the MPP under dynamic conditions.
3. Wireless Charging System Design
3.1 LCC-S Topology Analysis
The wireless charging system utilizes the LCC-S compensation topology, simplified as shown in Figure 5. Key components include:
- \(U_{\text {INV}}\): Inverter DC input voltage
- \(U_{\text {REC}}\): Rectifier DC output voltage
- \(L_T, L_R\): Self-inductances of transmitter and receiver coils
- \(M_{\text {TR}}\): Mutual inductance between coils
- \(C_T, C_R, L_F, C_F\): Compensation components
At resonance, the system satisfies:\(L_F C_F = L_R C_R = (L_T – L_F) C_T = \frac{1}{\omega^2} \quad (3)\) where \(\omega\) is the resonant frequency. Using the fundamental harmonic approximation, the equivalent resistance \(R_{\text {EQ}}\) and AC voltages are:\(\left.\begin{array}{l} R_{\text {EQ}} = \frac{8}{\pi^2} R_L \\ U_T = \frac{2\sqrt{2}}{\pi} U_{\text {INV}} \\ U_R = \frac{2\sqrt{2}}{\pi} U_{\text {REC}} \end{array}\right\} \quad (4)\) where \(R_L\) is the load resistance.
3.2 Coil Design and Simulation
Coil parameters were optimized using Maxwell simulations. Table 1 summarizes the self-inductance and mutual inductance for different turns at a 6 mm air gap:
| Air Gap (mm) | Turns | \(L_R\) (μH) | \(M_{\text {TR}}\) (μH) | \(L_T\) (μH) |
|---|---|---|---|---|
| 6 | 5 | 4.410 | 2.337 | 4.413 |
| 6 | 7 | 7.213 | 4.105 | 7.228 |
| 6 | 9 | 10.092 | 6.019 | 10.091 |
| 6 | 11 | 12.801 | 7.889 | 12.853 |
| 6 | 13 | 15.301 | 9.645 | 15.306 |
| 6 | 15 | 17.319 | 11.117 | 17.360 |
Higher turns increase self-inductance and mutual inductance, so 15-turn coils were selected for optimal performance.
3.3 Electrical Characteristics
Under resonance, the output voltage and power are:\(U_R = \frac{M_{\text {TR}}}{L_F} U_T \quad (5)\)\(P_{\text {OUT}} = \left(\frac{M_{\text {TR}}}{L_F}\right)^2 \frac{U_T^2}{R_{\text {EQ}}} \quad (6)\) The system exhibits constant voltage characteristics, as \(U_R\) is independent of \(R_{\text {EQ}}\), while \(I_R\) is inversely proportional to \(R_{\text {EQ}}\).
4. Experimental Validation
4.1 PV System Experiment
The Boost converter experiment used \(U_s = 10 \, \text{V}\), \(D = 0.68\), \(R = 45 \, \Omega\), and \(f_s = 50 \, \text{kHz}\). Measured results:
- Output voltage \(U_o = 30 \, \text{V}\) (theoretical: 31.25 V), with a 1.25 V loss due to component imperfections.
- Output power \(P = 20 \, \text{W}\).
Waveforms in Figure 6 show the switch voltage, input current, and output voltage, confirming the converter’s operation.
4.2 Wireless Charging Experiment
Using the LCC-S topology with 15-turn coils, experimental results at 85 kHz were:
- Input: \(U_T = 30.09 \, \text{V}\), \(I_F = 2.49 \, \text{A}\)
- Output: \(U_R = 15.05 \, \text{V}\), \(I_R = 4.18 \, \text{A}\)
- Efficiency:\(\eta = \frac{U_R I_R}{U_T I_F} = \frac{15.05 \times 4.18}{30.09 \times 2.49} \approx 83.96\%\)
Current waveforms in Figure 7 confirm power transfer between the transmitter and receiver coils.
4.3 Integrated System Performance
Combining the PV and wireless modules, the MPPT algorithm successfully tracked the MPP under varying light conditions (Figure 8). PV output voltage and current waveforms in Figure 9 show rapid adaptation to light intensity changes, validating the system’s overall efficiency.
5. Conclusion
This study presents a robust experimental platform for PV-powered wireless charging of electric vehicles. Key achievements include:
- Design of a DSP28335-controlled system integrating PV generation and LCC-S wireless charging.
- Validation of MPPT performance using the P&O algorithm under dynamic conditions.
- Successful power transfer via the LCC-S topology with an efficiency of ~84%.
The platform serves as an effective teaching and research tool, enabling students to understand EV charging technologies, PV systems, and wireless power transfer. Future work may focus on optimizing coil designs and exploring hybrid energy storage systems for enhanced reliability.