# Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines

^{*}

## Abstract

**:**

## 1. Introduction

#### 1.1. Motivation

#### 1.2. Preliminary Work

#### 1.3. Outline of the Paper

## 2. Machine Model

#### 2.1. Permanent Magnet Synchonous Machine Model

#### 2.2. Parameter Identification

#### 2.3. Time-Discrete Model Equations

#### 2.4. Inverter- and Iron-Losses

## 3. Control Algorithm

#### 3.1. Simulation Environment

#### 3.2. Basic Principle of the Predictive Current Control

#### 3.2.1. Operation Area Constraints

#### 3.2.2. Current-, Flux-Linkage-, and Voltage-Planes

#### 3.2.3. Timing of the Digital Control

#### 3.2.4. Prediction of the Reachable Operational Area

#### 3.3. Online Torque Reference Calculation and Control

#### 3.3.1. Dynamic Operation

#### 3.3.2. Stationary Operation

#### 3.4. Simulation Results

## 4. Test-Setup

#### 4.1. Device-Under-Test

#### 4.2. Test-Bench Setup

## 5. Measurement Results

#### Test-Bench Measurement

## 6. Discussion and Conclusions

#### 6.1. Parameteridentification and Modelling

#### 6.2. Introduced Control Algorithm

#### 6.3. Results

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Han, Z.; Liu, J.; Yang, W.; Pinhal, D.B.; Reiland, N.; Gerling, D. Improved Online Maximum-Torque-Per-Ampere Algorithm for Speed Controlled Interior Permanent Magnet Synchronous Machine. IEEE Trans. Ind. Electron.
**2020**, 67, 3398–3408. [Google Scholar] [CrossRef] - Tinazzi, F.; Bolognani, S.; Calligaro, S.; Kumar, P.; Petrella, R.; Zigliotto, M. Classification and review of MTPA algorithms for synchronous reluctance and interior permanent magnet motor drives. In Proceedings of the 2019 21st European Conference on Power Electronics and Applications (EPE ’19 ECCE Europe), Genova, Italy, 3–5 September 2019; pp. 1–10. [Google Scholar]
- Wang, J.; Huang, X.; Yu, D.; Chen, Y.; Zhang, Y.; Niu, F.; Fang, Y.; Cao, W.; Zhang, H. An Accurate Virtual Signal Injection Control of MTPA for an IPMSM With Fast Dynamic Response. IEEE Trans. Power Electron.
**2018**, 33, 7916–7926. [Google Scholar] [CrossRef] [Green Version] - Lee, G.-H.; Kim, S.-I.; Hong, J.-P.; Bahn, J.-H. Torque Ripple Reduction of Interior Permanent Magnet Synchronous Motor Using Harmonic Injected Current. IEEE Trans. Magn.
**2008**, 44, 1582–1585. [Google Scholar] [CrossRef] - Nishio, T.; Ryosuke, Y.; Masahiko, K.; Akatsu, K. A Method of Torque Ripple Reduction by Using Harmonic Current Injection in PMSM. In Proceedings of the 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), Singapore, 25–28 November 2019; pp. 1–5. [Google Scholar]
- Li, S.; Han, D.; Sarlioglu, B. Modeling of Interior Permanent Magnet Machine Considering Saturation, Cross Coupling, Spatial Harmonics, and Temperature Effects. IEEE Trans. Transp. Electrific.
**2017**, 3, 682–693. [Google Scholar] [CrossRef] - Cho, H.-J.; Kwon, Y.-C.; Sul, S.-K. Optimal Current Trajectory Control of IPMSM for Minimized Torque Ripple. In Proceedings of the 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, USA, 19–21 June 2019; pp. 1–6. [Google Scholar]
- Farshadnia, M.; Cheema, M.A.M.; Dutta, R.; Fletcher, J.E.; Rahman, M.F. Detailed Analytical Modeling of Fractional-Slot Concentrated-Wound Interior Permanent Magnet Machines for Prediction of Torque Ripple. IEEE Trans. Ind. Applicat.
**2017**, 53, 5272–5283. [Google Scholar] [CrossRef] - Richter, J.; Doppelbauer, M. Predictive Trajectory Control of Permanent-Magnet Synchronous Machines with Nonlinear Magnetics. IEEE Trans. Ind. Electron.
**2016**, 63, 3915–3924. [Google Scholar] [CrossRef] - Krause, P.C.; Wasynczuk, O.; Sudhoff, S.D. Analysis of Electric Machinery and Drive Systems; Wiley-Interscience: Hoboken, NJ, USA; IEEE Press: New York, NY, USA, 2002. [Google Scholar]
- Pinto, D.E.; Pop, A.-C.; Kempkes, J.; Gyselinck, J. Dq0-modeling of interior permanent-magnet synchronous machines for high-fidelity model order reduction. In Proceedings of the 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), Brasov, Romania, 25–27 May 2017; pp. 357–363. [Google Scholar]
- Štumberge0r, G.; Štumberger, B.; Marčič, T. Magnetically Nonlinear Dynamic Models of Synchronous Machines and Experimental Methods for Determining their Parameters. Energies
**2019**, 12, 3519. [Google Scholar] [CrossRef] [Green Version] - Richter, J.; Doppelbauer, M. Control and mitigation of current harmonics in inverter-fed permanent magnet synchronous machines with non-linear magnetics. IET Power Electron.
**2016**, 9, 2019–2026. [Google Scholar] [CrossRef] - Decker, S.; Rollbühler, C.; Rehm, F.; Brodatzki, M.; Oerder, A.; Liske, A.; Kolb, J.; Braun, M. Dq0-modelling and parametrization approaches for small delta connected permanent magnet synchronous machines. In Proceedings of the 2020 International Conference on Power Electronics, Machines and Drives (PEMD 2020), Nottingham, UK, 15–17 December 2020. [Google Scholar]
- Decker, S.; Foitzik, S.; Rehm, F.; Brodatzki, M.; Rollbühler, C.; Kolb, J.; Braun, M. DQ0 Modelling and Parameterization of small Delta connected PM Synchronous Machines. In Proceedings of the 2020 International Conference on Electrical Machines (ICEM), Göteborg, Sweden, 23–26 August 2020. [Google Scholar]
- Richter, J.; Dollinger, A.; Doppelbauer, M. Iron loss and parameter measurement of permanent magnet synchronous machines. In Proceedings of the 2014 International Conference on Electrical Machines (ICEM), Berlin, Germany, 2–5 September 2014; pp. 1635–1641. [Google Scholar]
- Richter, J.; Winzer, P.; Doppelbauer, M. Einsatz Virtueller Prototypen bei der Akausalen Modellierung und Simulation von Permanenterregten Synchronmaschinen. Application of Virtual Prototypes of Permanent Magnet Synchronous Machines by Acausal Modeling and Simulation; VDE-Verlag: Berlin, Germany, 2013. [Google Scholar]
- Axtmann, C.; Boxriker, M.; Braun, M. A custom, high-performance real time measurement and control system for arbitrary power electronic systems in academic research and education. In Proceedings of the 2016 18th European Conference on Power Electronics and Applications (EPE’16 ECCE Europe), Karlsruhe, Germany, 5–9 September 2016; pp. 1–7. [Google Scholar]
- Schwendemann, R.; Decker, S.; Hiller, M.; Braun, M. A Modular Converter- and Signal-Processing-Platform for Academic Research in the Field of Power Electronics. In Proceedings of the 2018 International Power Electronics Conference (IPEC-Niigata 2018 -ECCE Asia), Niigata, Japan, 20–24 May 2018; pp. 3074–3080. [Google Scholar]

**Figure 1.**Result of the reference torque calculation. The x-axis denotes the direct current, the y-axis the quadrature current. The torque hyperbolas (iso-torque curves) in grey are calculated considering the machines flux-linkages and currents. The maximum current magnitude is the red dotted circle. The maximum torque per ampere (MTPA) locus for maximum torque at minimum current is the solid red line. The maximum torque per volt/voltage (MTPV) locus for maximum torque at constrained voltage is the solid blue line.

**Figure 3.**Finite element analysis (FEA)-calculated flux-linkages for the used machine in simulation and for the explanations, assuming $\omega =\mathrm{const}.$ at a fixed rotor position $\gamma $ : (

**a**) flux-linkage of the direct-axis (

**b**) flux-linkage of the quadrature-axis. The displayed data are of a machine with a maximum speed up to $15.000\mathrm{rpm}$ at $70\mathrm{kW}$ peak power at a voltage of $300{\mathrm{V}}_{\mathrm{DC}}.$

**Figure 4.**Different planes: (

**a**) current plane; (

**b**) flux-linkage plane; (

**c**) voltage plane. The planes (

**a**), (

**b**), and (

**c**) are showing the latest operating point (small black circle). The reachable operating points inside the blue hexagon and chosen trajectory considering of each time-step and voltage hexagon (purple star). The current limitation of the machine is marked as red circle. In (

**c**) also the rotating inverter voltage hexagon with the black inner circle is drafted.

**Figure 5.**Visualization of the different control periods with sampling, prediction, and reference value calculation within the control procedure.

**Figure 7.**Torque plane (z-axis) at present current, speed and rotor position. The gradient of the ideal reference torque trajectory is the black line, the actual torque the black circle. The boundaries are marked as blue voltage hexagon and the chosen next reference value is in purple. The reference torque is the red star with the offline calculated red MTPA trajectory for ideal steady-state operation.

**Figure 8.**Calculation of the ideal reference value considering the gradient $\nabla k$ with $\left\{\frac{\mathsf{\Delta}T}{\mathsf{\Delta}\psi}\right\}$ under the certain constraints. The purple arrow shows the chosen reference value with optimal trajectory.

**Figure 9.**Dynamic case: (

**a**) and (

**b**) torque contour lines (z-axis) and constraint area due to the applicable voltage hexagon in blue, present value as black circle. In (

**a**) the current plane (x- and y-axis) is shown, (

**b**) shows it in the equivalent flux linkage plane. The purple arrow shows the chosen reference value from Figure 8 with fastest achievable torque for the next control period.

**Figure 10.**Stationary case (first iterations of two): With torque contour lines (surface) and constraint area due to the applicable voltage hexagon in blue and the current limit in red. (#1) to (#3) are the values for the polynomial approximation, (*) is the solution of the first iteration of the polynomial approximation. As visible, the first approximation of the iso-torque curve (purple) does not suit the iso-torque curve, another iteration is necessary. The x- and y-axis are the direct and quadrature currents.

**Figure 11.**Supporting points with intersection to the hexagonal area: Both diagrams with reference torque in black, present torque (iso-curve) in green. (

**a**) hexagon edges with corresponding torque intersection. As shown in Figure 10 both hexagon edges (2 and 3) with the chosen supporting point (d- and q-current) marked with the purple cross and the green circle. (

**b**) shows the selection of the desired value by considering the sign and the intersection of the reference torque with the different iterations displayed with black arrows. As a result, the desired value is identified as purple cross and the green circle similar to Figure 10.

**Figure 12.**Stationary case: (

**a**) Second order polynomial approximated d- and q-current (red dashed line). The supporting points are marked with black circles, the solution of the minimization problem (

**b**) is marked as star. (

**b**) shows the minimization problem as described in (20).

**Figure 13.**Stationary case with two iterations: The area, which is attainable within the control period is enclosed by the blue hexagon. The current limit is displayed in red. The surface describes the machine torque. Both iterations of the polynomial approximation are shown in purple. The first iteration (Figure 10) does not match the iso-torque curve, where the second iteration matches well with the green iso-torque curve within the range of interest.

**Figure 14.**Simulation setup with 500 rpm in the beginning and increased after 0.02 s to 7000 rpm for the operation at field-weakening. In Figure 15 is the corresponding torque displayed.

**Figure 15.**Operation of the control algorithm at two different torques. The corresponding speed is shown in Figure 14. The torque T, controlled with the introduced algorithm, is shown in black, the torque for control with equivalent constant currents ${T}_{\mathrm{rip}.}$ is shown in light brown.

**Figure 16.**Simulation of the trajectory in red at 30 Nm and 500 rpm, with the red dots at dynamic operation and the red crosses at stationary operation. In blue at 15 Nm and 7000 rpm, with the blue dots at dynamic operation and the blue crosses at stationary operation. The orange crosses show the behavior during changing the speed.

**Figure 17.**Torque control with a fundamental predictive control algorithm and pre-calculated reference values in (

**b**) the controlled currents to the corresponding torque (

**a**) are displayed. In (

**c**) the torque of the introduced algorithm is shown in brown. The minimized torque ripple is displayed black. (

**d**) shows the corresponding online calculated currents including the current ripple needed for the minimization of the torque ripple. The simulations were done at 600 rpm rotor speed.

**Figure 18.**Measured/estimated flux-linkages of the device under test at the test-bench, assuming $\omega =1000\mathrm{rpm}$ at a fixed rotor position $\gamma =60\xb0$: (

**a**) flux-linkage of the direct-axis (

**b**) flux-linkage of the quadrature-axis.

**Figure 19.**Test-bench setup: (

**a**) Testbench cabinet with inverters and signal processing; (

**b**) mechanical assembly of device under test and load machine (Source: Amadeus Bramsiepe, KIT).

**Figure 20.**Torque step from zero torque to $2\mathrm{Nm}$ at $500\mathrm{rpm}$. The reference torque is thereby displayed black, the present inner torque (according Equation (5)) calculated as describe before is brown. The predicted torque used in the control is shown as purple line. The torque in this operational point, controlled with equivalent constant currents (as is done in fundamental approaches without torque ripple compensation) is shown as green dashed line.

**Figure 21.**Current plane (

**a**) and flux-linkage plane (

**b**) with the currents/flux-linkages at each time step. The values form bottom right to the left show the gradient search algorithm. After the intersection with the iso-torque curve the stationary case is applied. The heap of the values is due to the stationary torque ripple compensation.

**Figure 22.**Stationary operation close to the nominal speed with $1000\mathrm{rpm}$ at $2\mathrm{Nm}$. In brown: the inner torque applied by the introduced control. In green the torque with uncompensated ripple, controlled with equivalent constant. Black shows the reference torque.

**Figure 23.**Measurement and equivalent simulation of (

**a**) current response (measurement in green and purple, simulation in red and blue) and (

**b**) torque response (measurement in brown, reference torque in black and simulation in green) at a rotor speed of 500 rpm.

**Figure 24.**Rotor speed of the measurement in green and constant rotor speed of 500 rpm in the simulation.

Quantities | Symbol | Value |
---|---|---|

Maximum voltage | $v$ | $48\mathrm{V}$ |

Maximum current | $i$ | $16\mathrm{A}$ |

Nominal speed | $n$ | $1000\mathrm{rpm}$ |

Nominal torque | $T$ | $3.3\mathrm{Nm}$ |

Permanent magnet flux-linkage | ${\psi}_{\mathrm{PM}}$ | $70.1\mathrm{mVs}$ |

Stator resistance | $R$ | $340\mathrm{m}\mathsf{\Omega}$ |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Decker, S.; Brodatzki, M.; Bachowsky, B.; Schmitz-Rode, B.; Liske, A.; Braun, M.; Hiller, M.
Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines. *Energies* **2020**, *13*, 5327.
https://doi.org/10.3390/en13205327

**AMA Style**

Decker S, Brodatzki M, Bachowsky B, Schmitz-Rode B, Liske A, Braun M, Hiller M.
Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines. *Energies*. 2020; 13(20):5327.
https://doi.org/10.3390/en13205327

**Chicago/Turabian Style**

Decker, Simon, Matthias Brodatzki, Benjamin Bachowsky, Benedikt Schmitz-Rode, Andreas Liske, Michael Braun, and Marc Hiller.
2020. "Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines" *Energies* 13, no. 20: 5327.
https://doi.org/10.3390/en13205327