AI BMS for Acceleration Detection & Battery Optimization
Budget: $250 – $750 USD
This project seeks an expert in AI and Battery Management Systems (BMS) to create comprehensive documentation.
The main aims are:
- Detecting sudden acceleration, specifically rapid increases in speed
- Implementing a battery optimization function.
The ideal BMS will balance energy consumption across all vehicle systems to ensure optimum performance and efficiency. Applicants should have substantial understanding of AI systems and battery management, with a focus on creating in-depth documentation. Previous experience in electric vehicles (EVs) is a considerable advantage.
Key Skills & Experience:
- Proficient in AI and BMS
- Excellent technical writing skills
- Knowledge in EVs, including acceleration or speed control.
You should base your documentation on strategies including agents that will act decision maker in real-time from mapping the decision from state to action. Create the state and action space, state transition and rewards to achieve the training goal.
Deliverables;
Documentation including backgrounds, tech trees, methods for data collection/feature extraction/detection model/threashold definition/RT monitoring/integration of BMS.
Illustrations, block diagrams, sample dataset, tables and summary.
The main aims are:
- Detecting sudden acceleration, specifically rapid increases in speed
- Implementing a battery optimization function.
The ideal BMS will balance energy consumption across all vehicle systems to ensure optimum performance and efficiency. Applicants should have substantial understanding of AI systems and battery management, with a focus on creating in-depth documentation. Previous experience in electric vehicles (EVs) is a considerable advantage.
Key Skills & Experience:
- Proficient in AI and BMS
- Excellent technical writing skills
- Knowledge in EVs, including acceleration or speed control.
You should base your documentation on strategies including agents that will act decision maker in real-time from mapping the decision from state to action. Create the state and action space, state transition and rewards to achieve the training goal.
Deliverables;
Documentation including backgrounds, tech trees, methods for data collection/feature extraction/detection model/threashold definition/RT monitoring/integration of BMS.
Illustrations, block diagrams, sample dataset, tables and summary.