Reliance RS60 Drones Mission feasibility assessment - asses what missions or use cases are possible or not using a go/no-go decision using simulation.
Explore the Reliance RS60 cell for drones, designed for mission feasibility assessments, ensuring optimal performance and reliability in various scenarios.
Value Propositions
Cylindrical 21700 form factor for compact design.
Nominal capacity of 21.6 Wh and 6.0 Ah for reliable energy supply.
Top-quartile volumetric power density of 7149 W/l for high performance.
Gravimetric energy density of 302 Wh/kg for lightweight applications.
Maximum continuous discharge of 50 A for demanding missions.
About the Cell
The Reliance RS60 is a cylindrical 21700 cell with a nominal capacity of 21.6 Wh and 6.0 Ah. It features a volumetric energy density of 858 Wh/l, which is significantly above the database median of 542 Wh/l, making it suitable for high energy density drone applications. The gravimetric energy density of 302 Wh/kg also places it in the top quartile compared to the median of 210 Wh/kg, ensuring that drones can operate efficiently without excessive weight. Additionally, the RS60 boasts a volumetric power density of 7149 W/l, which is among the highest in the database, allowing for rapid energy delivery during critical flight phases. With a maximum continuous discharge rate of 50 A, this cell is designed to meet the high demands of drone operations, particularly in challenging environments. The RS60's design optimally balances energy capacity and power output, making it an ideal choice for UAV battery pack design and drone battery cell selection.
Application Challenges
In the context of drones, mission feasibility assessment is crucial for determining what missions or use cases are possible. The ability to accurately predict battery performance under various conditions is essential for ensuring mission success. For instance, high energy density is vital for long endurance drone batteries, allowing for extended flight times without increasing weight. The RS60's nominal capacity of 21.6 Wh and high discharge rates are particularly beneficial for UAV applications that require reliable performance in demanding scenarios. Furthermore, understanding the thermal management of batteries is critical to prevent overheating, especially in high-stress missions. The RS60's design helps mitigate these risks, ensuring safe battery packs for UAVs and improving overall mission endurance.
Why this Cell
The Reliance RS60 cell is specifically designed to address the challenges faced in drone applications. Its maximum continuous discharge rate of 50 A is in the top quartile compared to the database median of 30 A, enabling it to handle high discharge rates required for demanding missions. The cell's volumetric energy density of 858 Wh/l is significantly above the median, allowing for lightweight drone battery packs that do not compromise on performance. This makes it an excellent choice for UAV battery optimisation, as it provides the necessary energy without adding unnecessary weight. Additionally, the RS60's high gravimetric power density of 2517 W/kg ensures that drones can achieve optimal powertrain efficiency, which is crucial for maintaining flight times and operational reliability.
How Model-Based Design Helps
Simulation and model-based design play a pivotal role in the selection and optimisation of battery cells for drones. By simulating load profiles, thermal behaviour, and voltage response, engineers can accurately predict how the Reliance RS60 will perform under various mission profiles. This allows for informed decision-making regarding cell selection, ensuring that the chosen battery can deliver the required thrust and energy throughout the flight envelope. For instance, modelling the thermal rise and internal temperature of the RS60 during high discharge scenarios helps prevent overheating and ensures safe operation. Furthermore, simulation enables the assessment of usable energy, allowing for precise go/no-go decision-making based on real-time battery state of charge (SoC) predictions. This level of analysis is essential for improving UAV mission endurance and ensuring that drones can reliably complete their missions, particularly in extreme environments.
