Japanese automaker Honda said Thursday it will invest JPY 10 trillion ($64.88 billion) in electrification and software over the 10 years running through the 2030 business year, Kallanish reports.

This is double the amount pledged in April 2022, ceo Toshihiro Mibe says in a press conference. He adds the company will spend JPY 1.19 trillion in R&D this year, mainly on vehicle intelligence and electrification, an on-year increase of 23%.

“As for strengthening software development, we realised the amount we had settled on two years ago was simply not enough, so we significantly increased that portion,” he adds.

The carmaker has also announced plans to reduce the procurement battery costs in North America by more than 20%, compared to current prices. “Honda will establish a competitive business structure with an aim to reduce overall production cost by approximately 35%,” it adds.

It has recently announced plans to build an integrated EV battery value chain in Canada, from resource processing to materials, cell production and recycling. Battery production in the country will be co-developed with GS Yuasa.

Under its strategy, seven EVs of various sizes will be launched globally by 2030. The company says it will also introduce a micro-mobility product, which will be equipped with four Honda Mobile Power Pack e: (MPPs) in Japan before the end of FY26, enhancing the applications of MPPs. The MPP is essentially a removable portable battery product.

Meanwhile, its electrification target of having 100% of its global sales as electric vehicles (including fuel cell electric vehicles) remains unchanged.

Earlier this week, the company inked a MOU with US tech firm IBM to develop joint R&D on semiconductor and software technologies for future software-defined vehicles (SDVs).

The two companies expect SDVs to require significantly higher design complexity, processing performance, and corresponding power consumption of semiconductors compared to conventional mobility products.

They will explore open and flexible software solutions, and optimise performance of semiconductor chips while reducing power consumption to get ready for the acceleration in artificial intelligence technology applications expected from 2030.