Journal
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
Volume 7, Issue 3, Pages 1482-1492Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TTE.2021.3059238
Keywords
Torque; Resistance; Mathematical model; Couplings; Stator windings; Windings; Computational modeling; Cross-coupling inductance; gradient descent; interior permanent magnet synchronous machine (IPMSM); maximum-torque-per-ampere (MTPA); maximum-torque-per-square-ampere (MTPSA) control; MTPA; MTPSA angle detection
Funding
- Key-Area Research and Development Program of Guangdong Province [2020B0909040004, 2020B090920002]
- Fundamental Research Funds for the Central Universities [20LGPY18]
- Guangdong Basic and Applied Basic Research Foundation [2020A1515110697]
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This article introduces an efficient MTPSA control for IPMSMs, aiming to maximize the ratio of output torque to the square of stator current without requiring machine parameters. The proposed control utilizes a gradient descent algorithm to find the optimal MTPSA angle, based on available measurements.
This article proposes an efficient maximum-torque-per-square-ampere (MTPSA) control for the interior permanent magnet synchronous machines (IPMSMs). The objective of the MTPSA control is to find the optimal current angle, denoted as MTPSA angle, to maximize the ratio of the output torque to the square of the stator current. The proposed MTPSA control is equivalent to the maximum-torque-per-ampere (MTPA) control, but it can eliminate the need of machine parameters and thus is independent of parameter variation. This article first derives the MTPSA control objective from the machine model considering cross-coupling inductances. Then, computation-efficient gradient descent algorithm is employed to detect the MTPSA angle from the derived objective. The proposed MTPSA control is based on available measurements without the need of machine parameters and invasive signal injection, which has not been simultaneously achieved in existing MTPA controls. The proposed control is validated with simulations, experiments, and comparisons with existing approaches on a laboratory IPMSM.
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