Enhancing EV Battery Recycling Through Discharge Optimization
| dc.contributor.author | Burman, Adam | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för elektroteknik | sv |
| dc.contributor.examiner | Zou, Changfu | |
| dc.contributor.supervisor | Yuan, Meng | |
| dc.date.accessioned | 2024-11-13T15:22:42Z | |
| dc.date.available | 2024-11-13T15:22:42Z | |
| dc.date.issued | 2024 | |
| dc.date.submitted | ||
| dc.description.abstract | Abstract The use of lithium-ion (Li-ion) batteries for electric vehicles (EVs) has increased exponentially and is expected to continue growing with the electrification of transportation. The increased usage of Li-ion batteries poses new challenges for reusing materials and improving the efficiency of battery recycling. Battery modules from electric vehicles that have reached their end of life (EOL) are fully discharged prior to recycling and minimizing discharge time is crucial for the industry. This study evaluates discharge current profiles generated by control strategies based on discharge time and the ability to maintain a safe internal battery temperature. The evaluation is performed using Simulink models of a table-based battery cell and a battery module representing a module in a 12s2p configuration based on the LG Chem E78 battery pouch cell. The controllers tested include constant current constant voltage (CC-CV), constant current constant temperature (CC-CT), dynamic programming (DP), and robust model predictive control (MPC). The results indicate that to avoid violating temperature constraints, controllers using model-based prediction and incorporating real-time measurement data with a Kalman filter, such as robust MPC, achieve the shortest discharge time without violating temperature constraints, showing promise for future applications. | |
| dc.identifier.coursecode | EENX30 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12380/308981 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | Technology | |
| dc.subject | Keywords: Discharge Time Optimization, Temperature Constraint, Robust Model Predictive Control (MPC), Proportional-Integral (PI) Control, Battery Modeling. | |
| dc.title | Enhancing EV Battery Recycling Through Discharge Optimization | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Systems, control and mechatronics (MPSYS), MSc |