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Reinforcement Learning Based Efficiency Optimization Scheme for the DAB DC–DC Converter With Triple-Phase-Shift Modulation
- Source :
- Tang, Y, Hu, W, Xiao, J, Chen, Z, Huang, Q, Chen, Z & Blaabjerg, F 2021, ' Reinforcement Learning Based Efficiency Optimization Scheme for the DAB DC-DC Converter with Triple-Phase-Shift Modulation ', I E E E Transactions on Industrial Electronics, vol. 68, no. 8, 9138774, pp. 7350-7361 . https://doi.org/10.1109/TIE.2020.3007113
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Aim to improve the power efficiency of the dual-active-bridge (DAB) dc–dc converter, an efficiency optimization scheme with triple-phase-shift (TPS) modulation using reinforcement learning (RL) is proposed in this article. More specifically, the Q-learning algorithm, as a typical algorithm of the RL, is applied to train an agent offline to obtain an optimized modulation strategy, and then the trained agent provides control decisions online in a real-time manner for the DAB dc–dc converter according to the current operating environment. The main objective is to obtain the optimal phase-shift angles for the DAB dc–dc converter, which can achieve the maximum power efficiency by reducing the power losses. Moreover, all possible operation modes of the TPS modulation are considered during the offline training process of the Q-learning algorithm. Thus, the cumbersome process for selecting the optimal operation mode in the conventional schemes can be circumvented successfully. Based on these merits, the proposed efficiency optimization scheme using the RL can realize the excellent performances for the whole load conditions and voltage conversion ratios. Finally, a 1.2-KW prototyped is built, and the simulation and the experimental results demonstrate that the power efficiency can be improved by using the optimization scheme based on the RL.
- Subjects :
- Reinforcement Learning (RL)
Maximum power principle
Computer science
DAB DC-DC converter
020208 electrical & electronic engineering
02 engineering and technology
Inductor
Power (physics)
Control and Systems Engineering
Modulation
Control theory
Q-learning
0202 electrical engineering, electronic engineering, information engineering
Reinforcement learning
Electrical and Electronic Engineering
power efficiency
optimization
Phase modulation
Electrical efficiency
Voltage
Subjects
Details
- ISSN :
- 15579948 and 02780046
- Volume :
- 68
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industrial Electronics
- Accession number :
- edsair.doi.dedup.....03573731415fc3dc1834ac01d240bd9d