Novel AI-powered solar panels offer 88% energy efficiency

The model can help improve solar output and motor efficiency by an extra 10 percent compared to real-world conditions.
Ameya Paleja
Artist's representation of an EV that does not need to be plugged in
Artist's representation of an EV that does not need to be plugged in


Researchers at the Odisha University of Technology and Research in India have developed an artificial intelligence (AI) powered model for direct current (DC) electric motors that are powered by photovoltaic arrays and do not need to be plugged into the grid for charging. In the future, such motors can be used at an industrial scale or for appliances at home, or even electric cars, IEEE Spectrum reported.

Solar-powered electric motors offer a way for electrical devices to switch to cleaner sources of power and be independent of the grid. The setup typically requires the use of a battery that can store excess energy generated by the photovoltaic cell and use it to power the motor when sunlight is not available.

Real-world DC motors have recorded energy efficiencies as high as 80 percent. However, with a solar array output optimized using AI, the Indian researchers were successful in reaching efficiencies as high as 88 percent. The team was also able to improve the efficiency by introducing a regenerative braking system into the mix that allowed the battery to charge again from the energy recovered from the braking.

Getting more from solar cells

For a given amount of irradiation, solar cells can produce a maximum amount of electrical power, referred to as a maximum power point. Along with sunlight, the maximum power point also varies by temperature. Therefore, solar cells always deliver much lower power than the maximum power point.

One way to change this is to lower the resistance of the solar cells, which increases the power that is generated. Researcher Bismit Mohanty and his team built a MATLAB model where they trained a neural network to determine solar cell resistance that would yield maximum power points. The neural network used thousands of temperature and irradiance measurements to arrive at the figure that can deliver maximum power output.

Novel AI-powered solar panels offer 88% energy efficiency
Improving power output of solar cells could mean we need fewer of them

Unfortunately, being a neural network solution, we do not entirely know what criteria were used to determine this number.

EVs that do not need to be plugged

Mohanty and his team have just developed a computer model so far and the next step would be to put it into the real world and make a physical model. The approach does pave the way for developing EVs that do not need to be plugged in at all.

Companies such as Lightyear have also begun production of solar-powered vehicles. Improvements in technology can help in the development of cars that can not be solar-powered but also meet the performance standards set by EVs today.

Just like the EV revolution has spilled over to other areas, these solar-powered electric motors will also find applications in other areas. At home, these could power simpler devices like refrigerators and fans, whereas in the industry they could also do some heavy lifting, where we rely on fossil fuels.

The researchers presented their findings at the  2023 International Conference on Smart Systems for Applications in Electrical Sciences.

Study Abstract

Modern drive technology is advancing significantly influenced by brushless DC motors, also known as BLDC Motors. A growing number of industries, including consumer appliances, the automobile sector, advance industrial automation, chemical and medical, instrumentation and aerospace, have embraced them due to their quick rise in popularity. This paper proposes a detailed study on BLDC motor powered by solar photovoltaic (SPV) array with an intelligent hybrid system of battery as backup. An artificial neural network (ANN) associated with maximum power point tracking (MPPT) is a method which is implemented in the solar photovoltaic system in order to harness the maximum power from the SPV panel during variable irradiance which naturally occurs because of bad climate. Through a buck-boost DC-DC converter, an automated power transfer for the battery is made possible by a bidirectional charging control. Speed control of BLDC motor is carried on using a voltage source inverter (VSI) which is fired by gating pulses which are generated out of the electrical commutation process of hall signals of the motor. Additionally, the concept of regenerative braking of BLDC motor is executed for power recovery in the battery which can be further used in future. All the performance analysis of PV array, battery and BLDC motor are carried out in MATLAB/Simulink platform.

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