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AI Maglev Trains: The Inspiration for Maglev Cars


AI Maglev Trains: The Inspiration for Maglev Cars
Illustration: ? IoT For All

Derived from the Latin word “Levitas” which means “lightness,” the term levitation indicates the rising or lifting of a person or thing by unnatural means. It is the process by which an object is held aloft, in a stable position, without mechanical support or physical contact. Magnetic levitation trains, or maglev trains, are high-speed AI-enhanced trains that move by gliding above dedicated magnetic guideways without making any contact with the tracks. Maglev technology represents the realization of the 21st-century engineering vision of high-speed, magnetically propelled vehicles that can move from one place to another, without the maintenance and safety concerns associated with traditional railroads.

'Maglev technology is going to lead to the production of cheap and affordable cars and also usher in a ground-breaking technological innovation of the 21st century.' -Jude ChukwudozieClick To Tweet

Understanding Maglev Trains

Maglev, or floating trains, make use of two sets of electromagnets: one set repels and pushes the train up off the track, and another set moves the elevated train ahead. They travel at unbelievably high speeds because of the superconducting electromagnets, cooled to extreme temperatures, often through a cryogenic process. These electromagnets increase the power of the field up to 10 times, generating powerful magnetic fields that are able to levitate and propel the train. Maglev trains do not make any physical contact with the rail. They have the characteristics of non-contact and suspension operation, strong climbing ability, small turning radius, low noise, energy saving, and environmental protection features.

Operational Process

Magnetic levitation is achieved with the aid of three loops set in the guideway. The first loop provides an upward force that opposes gravitational pull and accounts for the hovering action of the train. The second loop stabilizes the object toward a home position while the third loop makes use of the attraction and repulsion forces of the magnet to keep the train moving along the guideway. When these loops are electrified through AC power, magnetic fields are generated. The field at the north poles pulls the train forward from the front while the field at the south poles pushes it forward from the rear enabling it to keep moving along its path. The superconducting electromagnets, permanent magnets, electrical power source, and metal coils that line a guideway are the component elements that generate the magnetic field. This is the basic idea and the driving principle behind maglev technology.

AI Use in Maglev Trains

Maglev trains are now self-driving, and this entails making use of AI’s neural networks to go wherever the programmed data network sends them. AI neural networks are computer algorithms used in machine learning that perform a function similar to the neurons in the human brain. They serve to achieve efficient routing, effectively changing the scheduling of the entire network to take any direction in real time. AI-enhanced algorithms and neural networks are required to manage and control high-speed maglev trains because human operators are incapable of handling the speed.

AI has been used to achieve breakthroughs in maglev train control, stability, and operational safety by overcoming the major drawbacks of instability and wobbling discomfort experienced with most maglev technology. Floating trains now offer smooth, safe, and seamless travel. AI is able to programmatically capture end-to-end maglev train workflows, including data preprocessing, selection, and testing. These programmatic workflows enable the system to regularly monitor and update its database. It also serves to improve real-time information and data exchange, thus increasing the system’s flexibility.

Merits of AI Maglev Trains

#1: High Speed & Fast Travel

Maglev trains are lighter with an even distribution of weight. This allows for high speed and quieter travel. With low mechanical breakdown, they undergo minimal guideway maintenance, unlike the traditional steel train which is subject to regular mechanical wear and tear.

#2: Improves Power Efficiency

Maglev trains do not experience friction or rolling resistance due to the lack of physical contact with the track. There is, however, air resistance and electromagnetic drag, brought about by the use of superconducting electromagnets, which reduces energy consumption and improves power efficiency.

#3: Minimizes Collision

Floating trains guarantee comfortable, smooth, and turbulent-free travel because they are driven along a powered guideway. They also move at the same speed, eliminating the possibility of a crash or collision. With maglev trains, derailment is also avoided. The further a maglev train moves away from its guideway, the stronger the magnetic force pushes it back into its place.

Disadvantages of Maglev Trains

Maglev trains move at very high speeds, and this raises grave concerns about the safety of passengers. Complications resulting in accidents will usually lead to high human fatalities. Maglev trains are much more expensive to construct than conventional trains because of the high number of superconducting electromagnets and permanent magnets required, which are usually very costly. Maglev trains do not make use of the conventional steel rail tracks and their existing infrastructure, but instead standalone track network systems designed for magnetic levitation and propulsion. The cost of this is also very high and capable of discouraging further research into the technology. Also, constant exposure to strong and large amounts of the electromagnetic field poses huge health risks not just to the nearby community but also to human operators and passengers alike.

Maglev Technology in Cars

Maglev trains provide inspiration for the innovation of Maglev cars, with China producing the first Maglev car which levitated 35 millimeters (about 1.4 inches) above dedicated magnetic highways. This feat was achieved by modifying a car with a permanent magnet array to float through a magnetic conductor rail track on the road. While this ride was not a particularly smooth and comfortable one due to the wobbling effect of the conductor rail along the magnetic path, there is, no doubt, a chance that the technology can be greatly improved.

Like China’s sky trains, there is a further need to reduce the electromagnetic radiation and amount of electricity that is required to propel the train. Stronger and more powerful chips as well as advanced semiconductor devices will help in finding a way to bring down the cost of Maglev trains. It is hoped that cars fitted with Maglev technology, expected to be a milestone advancement over the Chinese experiment, will soon arrive. With a high operating range, these cars will save a lot of energy in the future.

Perhaps something a little different and revolutionary will be the invention of Magnetic cars that can travel on roads. This will operate on the pull-push system of the magnetic field created by the superconducting and permanent magnets. Connecting the superconducting electromagnetic core bar to the front and back exteriors of the car wheel to create attraction and repulsion forces with the permanent magnet at the wheel will cause the car to move. Of course, AI will be adapted to control the functionalities of the vehicle. This technology will reduce the cost of running a car, eradicate environmental disasters caused by fossil fuel energy, and is presently the subject of my team’s research project.

The Future of Maglev

The future of Maglev technology is no doubt, Maglev cars. Thanks to Maglev trains for birthing this child of fate. Maglev technology is going to lead to the production of cheap and affordable cars and also usher in a ground-breaking technological innovation of the 21st century. A world where we are finally free from the contamination of fossil fuel-driven cars sounds perfect and appears ready to happen.

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  • Artificial Intelligence
  • Machine Learning
  • Rail and Railways
  • Rail Management
  • Transportation and Mobility

  • Artificial Intelligence
  • IoT Business Strategy
  • Machine Learning
  • Rail and Railways
  • Rail Management

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