China's first hydrogen-powered smart intercity electric multiple unit, the CINOVA H2, independently developed by CRRC Qingdao Sifang Co Ltd, is unveiled in Berlin, Germany, on Sept 24. [Photo provided to chinadaily.com.cn]

China's first hydrogen-powered smart intercity electric multiple unit, the CINOVA H2, independently developed by CRRC Qingdao Sifang Co Ltd, was unveiled in Berlin, Germany, on Sept 24, marking a significant breakthrough in the country's hydrogen-powered rail transport technology.

The train consists of four cars and is equipped with high-power hydrogen fuel cells with a capacity of 960 kilowatts, offering a maximum operating speed of 200 kilometers per hour.

"This train is powered by hydrogen fuel cells, generating electricity through the electrochemical reaction of hydrogen and oxygen, achieving zero carbon emissions throughout the full duration of its journey," said a representative of CRRC Qingdao Sifang.

The train's key performance metrics — such as speed, passenger capacity, and range — surpass its international counterparts, providing a new impetus for the green upgrade of passenger equipment on non-electrified railways, he added.

"As an innovative green rail transport vehicle, this train is a true 'environmental champion,'" added the representative.

The train produces no air pollutants, and based on an annual operational estimate of 300,000 km, each train can reduce carbon dioxide emissions by about 730 metric tons per year, equivalent to afforesting 567 mu, or 37.8 hectares.

The train also features an innovative recycling technology: a water emitted by the hydrogen fuel cell reaction is purified and recycled for passenger use, such as washing, while waste heat from the cooling system is reused to heat the train's air conditioning during winter.

Additionally, the train incorporates cutting-edge smart technologies, including digital twins, artificial intelligence, and 5G, to establish an advanced integrated operations and maintenance platform, enabling real-time monitoring, fault diagnosis, and maintenance decision-making for its full lifecycle management.