Target Current Modulation as a Novel Approach for Active Balancing in Automotive MMSPCs
A main challenge in the use of an automotive Modular Multilevel Series Parallel Converter (MMSPC) is combining high efficient operation alongside active balancing of the distributed batteries. To overcome this challenge a new modulation method is introduced. The aim of Target Current Modulation (TCM...
Saved in:
Published in | 2022 IEEE 23rd Workshop on Control and Modeling for Power Electronics (COMPEL) pp. 1 - 8 |
---|---|
Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
20.06.2022
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | A main challenge in the use of an automotive Modular Multilevel Series Parallel Converter (MMSPC) is combining high efficient operation alongside active balancing of the distributed batteries. To overcome this challenge a new modulation method is introduced. The aim of Target Current Modulation (TCM) is to have a high utilization of the total energy stored in the batteries and therefore, an extended range of the powered electric vehicle (EV). The TCM algorithm calculates an optimal switching state of the MMSPC to achieve a current distribution among the single modules which fits best the precalculated target currents for each battery. These target currents are a combination of a loss optimal current distribution and offset currents that are added to fulfill side conditions such as state of charge (SoC) balancing. Feasible battery current distributions are calculated by a model-predictive approach and evaluated in each control cycle. TCM is implemented on a field-programmable gate array (FPGA) and tested with a standardized automotive driving cycle on a test bench. |
---|---|
DOI: | 10.1109/COMPEL53829.2022.9830002 |