Source: Gasgoo
Karma Automotive announced a bilateral partnership with Intel Automotive to develop software-Defined Vehicle Architecture (SDVA) and use it as the infrastructure for its upcoming models. It will start with the 2026 Karma Kaveya supercar. In addition, the two companies will collaborate to demonstrate and validate key concepts to facilitate the development of SDVA open standards that can be shared publicly and commercially to support the transformation of the broader automotive industry.
According to foreign media reports, this partnership has now taken another important step forward. At CES 2025, Karma Automotive will partner with Intel Automotive to showcase one of the many ways Karma vehicles can benefit from SDVA: improved powertrain performance and range efficiency. In addition to demonstrating the SDVA powertrain, Karma Automotive will also work with Intel Automotive to demonstrate Intel’s combination of enhanced high-performance computing, intelligent power management, and software-defined partition controllers based on open ecosystem AI (artificial intelligence). To achieve a more sustainable, scalable and profitable automotive future.
Marques McCammon, President of Karma Automotive, said: “Karma Automotive’s SDVA technology, developed in partnership with Intel Automotive, will debut on the 1,000-plus horsepower Karma Kaveya model in 2026. The technology is a transformative technology that offers unmatched benefits in computing speed and power, upgradability and vehicle connectivity, ease of manufacturing, vehicle safety, and the powertrain performance and efficiency we demonstrated at CES. SDVA will revolutionize the Karma vehicle experience, and by building an open SDVA ecosystem with Intel Automotive, we will change software development practices for the benefit of the entire automotive industry.”
In addition, Karma will showcase its Intel co-branded inverter, which converts the direct current provided by the vehicle battery into alternating current, and will integrate Optimal Pulse Pattern programming to control the vehicle’s motor (EMotor) to improve vehicle efficiency. At the same time, Karma will demonstrate a simulation dynamic test, showing four driving modes – highway, city, park and charge, Hub Torque (NM), hub speed (RPM), power (W), and efficiency (%) data achieved by controlling Torque Ripple Reduction and Range Boost parameters for powertrain and energy telemetry are also displayed. In addition to Karma, information on energy savings (Wh) and range gains (Km) achieved through the above processes will be presented.
