Innovation in the automotive industry is of pivotal importance for European´s prosperity. OSEM-EV will provide solutions for better autonomy and predictable range to address today´s car buyers concern about electro mobility. Just increasing the battery capacity is not a viable option because the expectation is to have a familiar level of comfort and safe, eco and human oriented mobility at affordable costs. OSEM-EV will translate the foreseen project innovations into a customer value proposition. The highest priority is improved mileage and predictable range without adding further cost and weight. The negative impact of high and low ambient temperatures will be limited. Cars autonomy will be increased due to a reduction of at least 50% of energy used for passenger comfort and at least 30% for component cooling in extreme conditions compared to current FEVs. The consortium will focus on thermal and coupled electro-thermal energy substitution and harvesting and smart energy usage for cooling and heating of the passenger compartment and in-car infrastructure. OSEM-EV goes for novel electro-thermal architectures and control algorithms including thermal insulation, thermal storage, innovative heating and cooling approaches applied to the powertrain (battery, inverter and motor), battery life duration enhancement as a side effect of thermal management, electronic control of energy and power flows, energy efficiency of electrified accessories, energy substitution and harvesting functions. The consortium will take a radical approach, which does not only rely on improving the efficiency of subsystems but also focuses on their interoperability. By creating an electro-thermal network, most of the energy shall be reutilized, no matter if stored in mechanical, electrical or thermal form.

SHASAI targets the HW/SW security and AI-based high risk systems intersection, aiming to enhance the security, resilience, automated testing, and continuous assessment of AI systems. The rising interest in these systems makes them attractive targets for threat actors due to their complexity and valuable data. Ensuring the security of AI systems involves safeguarding AI models, datasets, dependencies, and securing the underlying HW/SW infrastructure. SHASAI takes a holistic approach of AI system security throughout their lifecycle stages. At requirement definition, SHASAI provides an enhanced risk assessment methodology for secure and safe AI. At design, SHASAI will propose secure and safe design patterns at SW and HW level to achieve trustworthy AI systems. During implementation, SHASAI provides tooling for a secure supply chain of the system by analyzing vulnerabilities in SW / HW dependencies, detecting poisoned data and backdoors in pretrained models, scanning for software vulnerabilities, hardening hardware platforms, and safeguarding intellectual property. At evaluation, SHASAI offers a virtual testing platform with automated attack and defense test suites to assess security against AI and infrastructure-specific threats. In operation, AI-enhanced security services continuously monitor the system, detect anomalies, and mitigate attacks using AI firewalls and attestation methods, ensuring availability and integrity. The feasibility of SHASAI methods and tools will be demonstrated in 3 real scenarios: 1. Agrifood industry: Cutting machines. 2. Health: Eye-tracking systems in augmentative and alternative communication. 3. Automotive: Tele-operated last mile delivery vehicle. Their heterogeneity and complementarity maximize the transferability of solutions. SHASAI will contribute to scientific, techno-economic, and societal impacts as it aligns with the CRA, EU AI Act, NIS2 and CSA, sharing and commercializing methods and tools to ensure trustworthy AI components.