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Direct voltage MTPA control of interior permanent magnet synchronous motor driven electric vehicles

2024· article· en· W4405098677 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueControl Engineering Practice · 2024
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsCarleton University
Fundersnot available
KeywordsElectric vehiclePermanent magnet synchronous motorMagnetControl (management)VoltageControl theory (sociology)Permanent magnet synchronous generatorSynchronous motorAutomotive engineeringEngineeringElectrical engineeringComputer sciencePhysicsPower (physics)

Abstract

fetched live from OpenAlex

This manuscript proposes an efficient, straightforward, direct voltage maximum torque per ampere (MTPA) control scheme for an interior permanent magnet synchronous motor (IPMSM) propelling an electric vehicle (EV). The main feature of the traction control scheme is that the MTPA is attained by directly varying the amplitude and angle of the voltage vector, eliminating the need for current control loops and associated regulators. Instead, a single-speed controller is adopted. Furthermore, an analytical formulation based on the motor voltage model is developed to extract the desired voltage’s magnitude and angle to run the motor within the MTPA operating points, disregarding numerical solutions, control law approximation, long-winded iterative calculations, or approximate representation of the IPMSM. Such a methodology significantly reduces control scheme complexity, enhances computational efficiency, and mitigates the delays associated with cascaded-based control systems. Additionally, it facilitates straightforward real-time implementation. The performance of the designed algorithm is experimentally validated using commonly adopted driving cycles, namely the Federal Test Procedure (US06) drive cycle and the New European Driving Cycle (NEDC). The validity test is performed using a 5 HP IPMSM. Based on the driving cycles employed, an intensive comparative evaluation against MTPA field-oriented control (FOC) is established. A quantitative assessment is conducted using the MTPA FOC as a benchmark to investigate energy consumption. This assessment reveals that the designed strategy achieved energy savings of 1.318% and 2.26% under US06 and NEDC, respectively, compared to the MTPA FOC. The proposed method’s speed-tracking accuracy and computational efficiency are also investigated and compared to the FOC and existing direct voltage approaches, demonstrating an average improvement of 14% in speed-tracking accuracy and 6.8% in computational efficiency. • A Simple direct voltage maximum torque per ampere control scheme is introduced. • Traditional cascaded current control loops are eliminated. • An average speed tracking improvement of 14% and energy savings of 2.26% is achieved. • The proposed method requires less time to be executed due to the direct calculation of its control signals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.200
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it