Energy-efficient Software-defined Evs (2ZERO Partnership)

Project results are expected to contribute to all the following outcomes:

• Demonstrated energy-efficient, electric Software Defined Vehicles (SDVs), with purposely developed and strategically positioned traction and chassis hardware (HW) subsystems leveraging opportunities of the software (SW) abstraction layers as the cornerstone of SDV, and overall scalable.
• Real life demonstration of the value of functional integration in terms of user value (ensuring travel time) and responsiveness to user and societal needs (e.g. reduced space needed for the vehicles, reduced consumption of resources, responsive to diverse user needs and abilities), charging infrastructure (vehicle-to-grid integration), cost (e.g. reducing development and integration effort, number, and specs for individual components), and energy demand (e.g. load shifting).
• Testing and validation of vehicle-to-grid (V2G) functionalities in real-world conditions to ensure efficient, interoperable and software-driven integration between SDVs, recharging infrastructure.
• Improved energy efficiency and increasing sustainability with optimal-sized batteries and long-trip capability with fast charging.
• Optimal integration and demonstration of HW and SW solutions along with standardised interfaces to enable affordable, mass-market EVs, such as but not limited to SDV application domains chassis/powertrain (e.g. vehicle size), body comfort and cockpit (maximizing the interior space, comfort and safety relative to the vehicle's exterior dimensions) to achieve efficient, compact designs with minimal and sustainable material use^[1].

In the past years a variety of road vehicle technologies on component and sub-system level (e. g. mechanical, electro-mechanical, electro-chemical, etc.) have been developed and offer the potential to be combined and improve user benefits at the embedded system level. The potential to further leverage these developments with Software Defined Vehicle solutions (e.g. high-level functionality ranging from energy efficiency and performance improvements to personalizing the driving experience) over the lifetime of the vehicle needs to be explored. This would bring together developers working at the embedded system level with those working on high-level functions also to ensure that novel solutions will conform with homologation requirements. Solutions coming from this project must also be compatible with current automotive standards, esp. regarding external infrastructure. Compatibility e.g. with EVSE regarding ISO 15118-20 must be ensured.

Proposed actions are expected to address all of the following aspects, where possible building upon available open-source building blocks:

• Investigate the potential of novel propulsion and chassis system/sub-systems packaging and performance from a holistic EV architecture perspective and for fast charging, significantly improving the current State-of-Art performance via digital solutions and leveraging AI when beneficial.
• Include chassis and traction hardware solutions as well as standardised control and physical interfaces to improve innovation speed and software solutions, also leveraging the potential of open source.
• Develop a system architecture to ensure optimal compatibility with the high-level SW and the physical powertrain and Electrical/Electronic (E/E) systems (e.g. mechanical, electro-mechanical, etc.) with appropriate SW tooling for efficient SDV development, integration and validation, e.g. operational functionality, also including driving range improvement according to user expectations. Target applications are expected to be fit for mass-market M1 C-segment vehicle or below.
• Identify required software interfaces (Application Programming Interface and/or software services), i.e. especially which kind of information/data are required for an energy-efficient in the context of powertrain, chassis, automated driving and vehicle SW/interfaces needed for vehicle-to-grid functionalities, considering the vehicle and environment.
• Develop solutions that minimize energy use while meeting users’ expectations, such as battery management, predictive maintenance, or eco-efficient routing and driving systems, leveraging AI-driven workflows when beneficial. When using AI-based approaches, projects are expected to ensure that the use AI in electric vehicles does not increase the overall energy need.
• Ensure the consistency of data and information from different sources and different market players to ensure the scaling potential of solutions (i.e. in-vehicle interfaces as part of the Vehicle Signal Specification, e.g. COVESA, Eclipse Software Defined Vehicle).^[2]
• Propose recommendations on possible test protocols for future implementation and safety ratings.
• Collaborate with the Software-defined Vehicle (SDV) initiative under the Chips JU^[3] by adopting relevant existing interfaces and building blocks, and proposing new ones developed within the project for potential inclusion in the SDV framework. Ensure close coordination with the European Connected and Autonomous Vehicle Alliance (ECAVA) announced in the European Automotive Action Plan.

This topic implements the co-programmed European Partnership on ‘Towards zero emission road transport’ (2ZERO). As such, projects resulting from this topic will be expected to report on the results to the European Partnership ‘Towards zero emission road transport’ (2ZERO) in support of the monitoring of its KPIs.

[1] Also see an example blueprint of a SDV in: https://federate-sdv.eu/wp-content/uploads/2024/04/2024-04-12-SDVoF-Vision-document-ver017-final.pdf

[2] COVESA, the Connected Vehicle Systems Alliance; Software Defined Vehicle | The Eclipse Foundation

[3] Projects Chips Ju