Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots
Abstract
:1. Introduction
- They may evolve in a forestry environment, as per the work proposed in [3], where the robot collects biomass samples and provides a dataset of different forest environments,
- They may also be aerial, such as the work proposed in [4], which uses an unmanned aerial vehicle (UAV) for cellular network relay inspection.
2. Dual Coulomb Counting Extended Kalman Filter Approach
Algorithm 1: Master microcontroller algorithm |
Algorithm 2: Slave microcontroller algorithm |
- For a non-null current, the slave microcontroller uses the CC function to monitor the SOC,
- For a null current, it uses the EKF function to update the SOC value.
Algorithm 3: Extended Kalman Filter Function |
3. Board Design
3.1. Components and Power Distribution
3.2. Master and Slave Microcontrollers Communication
4. Results
4.1. Performance Evaluation
4.2. Prototype Efficiency
4.2.1. Components Energy Consumption
4.2.2. Charging Process Efficiency
4.2.3. Discharging Process Efficiency
5. Discussion
6. Conclusions and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AEKF | Ascending extended Kalman filter |
AI | Artificial intelligence |
AUV | Micro autonomous underwater vehicle |
BMS | Battery management system |
CC | Coulomb counting |
DCC-EKF | Dual coulomb counting extended Kalman filter |
DEKF | Dual Extended Kalman Filter |
EKF | Extended Kalman filter |
I2C | Inter-Integrated Circuit |
KF | Kalman filter |
Li-NMC | Lithium Nickel Manganese Cobalt Oxid |
OCV | Open circuit voltage |
PCB | Printed circuit board |
SOC | State of charge |
SOH | State of health |
SOF | State of function |
UAV | Unmanned aerial vehicle |
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Parameters | Values |
---|---|
Covariance SOC | 2.5 × 10 |
Covariance | 0 |
Process noise SOC | 1 |
Process noise | 1 |
Measurement noise | 1 × 10 |
Sensor | Value |
---|---|
Voltage resolution (LM324N) | 100 mV |
Current resolution (ACS-712) | 40 mA |
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Chellal, A.A.; Gonçalves, J.; Lima, J.; Pinto, V.; Megnafi, H. Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots. Machines 2021, 9, 313. https://doi.org/10.3390/machines9120313
Chellal AA, Gonçalves J, Lima J, Pinto V, Megnafi H. Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots. Machines. 2021; 9(12):313. https://doi.org/10.3390/machines9120313
Chicago/Turabian StyleChellal, Arezki Abderrahim, José Gonçalves, José Lima, Vítor Pinto, and Hicham Megnafi. 2021. "Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots" Machines 9, no. 12: 313. https://doi.org/10.3390/machines9120313
APA StyleChellal, A. A., Gonçalves, J., Lima, J., Pinto, V., & Megnafi, H. (2021). Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots. Machines, 9(12), 313. https://doi.org/10.3390/machines9120313