FPGA-based sensorless control of brushless synchronous starter ...

FPGA-based sensorless control of brushless synchronous starter generator at standstill and low speed using high frequency signal injection for an aircraft application 1,4,5

Amira Maalouf1, Sandine Le Ballois2, Eric Monmasson3, Jean-Yves Midy4, Christophe Bruzy5

Thales-AES, 41 Boulevard de la république, 78400 Chatou, France, email: [email protected], [email protected], [email protected] 2,3 SATIE-IUP GEII, rue d’Eragny, 95031 Cergy-Pontoise, France, email: [email protected]², [email protected]

Abstract : The sensorless control of brushless synchronous starter generator (BSSG) that is widely used in the aeronautics domain is now considered a hot topic following to the success of the electric start-up of the main engine. Therefore, the focus of this paper is the position estimation of the BSSG during the electric start-up of the main engine at low speed and particularly at standstill. This is achieved by injecting a rotating high frequency voltage in the vector control scheme. The theoretical analysis is supported by experimental evidence obtained by using an aeronautic test bench. The sensorless algorithm is implemented on a Field Programmable Gate Array (FPGA) in order to ensure fast computation with an execution time of a few microseconds. Numerous experimental results are given in order to illustrate the efficiency of the used FPGA-based solution at low speed and at standstill to achieve good performance sensorless control of the brushless synchronous starter generator.

Keywords: Brushless synchronous starter/generator (BSSG), main starter/generator MSG, sensorless control, rotating high frequency signal injection. I. INTRODUCTION

W

ITH the introduction of the concept of the More Electric Aircraft, different power system functions may be allocated to electrical means such as the start-up of the main engine [1-2]. Therefore, the use of the brushless synchronous starter/generator (BSSG) that can ensure the start-up operation together with the power electric generation is a logical choice. However, the control of BSSG requires the rotor position information in order to provide synchronized phase excitation pulses and to generate the required motor torque. Usually, the information is provided by a resolver or an absolute encoder. Sensors increase the machine size and the cost of the drive. Moreover, they reduce the reliability of the system [3]. Consequently, the need of eliminating position or velocity transducers in motor motion applications has long been recognized. Many sensorless techniques were developed during the last two decades depending on the rotational speed of the machine. In this paper, the main focus is the study of the position estimation of the BSSG at low speed and even

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standstill since it is the most challenging region to estimate the rotor position. Different techniques were developed over the years to estimate the position in the low speed region and this by exploring the saliency aspect of the machine via either switching transients or carrier frequency signal injection [4]. In this paper, the carrier-signal-injection-based self-sensing is chosen since it makes use of the current sensors already present for current-control purposes and is simpler to realize by comparison to the switching transients. This is achieved by superimposing a high frequency signal to the fundamental one, that interacts with the machine saliency and causes phase or amplitude modulation in the response. The rotating high frequency signal can be whether current or voltage waveforms. In the current injection, it is difficult to increase the injection frequency to attain the high frequency characteristics of the machine [5]. Therefore, voltage injection scheme is preferred to the current injection scheme in this paper since it doesn't require a high bandwidth of the current controller [6]. Then, the rotor position is estimated by processing the modulated current using synchronous filtering. To demonstrate the performance of this solution, the sensorless controller is implemented on a FPGA board and tested with a 40 kVA BSSG. FPGAs are selected for this application since they ensure a fast computation time together and, as consequence, ensure a quasi-analog treatment. Different experimental tests were carried out on the used BSSG to prove the efficiency of the proposed controller and the results are given in this paper. This latter is organized as follows. At first, the brushless synchronous starter/generator is presented in section II. The principle of the high frequency injection is shown in section III. Then, the VHDL architecture of the high frequency sensorless controller is treated in section IV. Finally, experimental results are shown in section V in order to illustrate the efficiency of the proposed EKF in estimating the rotor position of machines for aircraft use. II. PRESENTATION OF THE BSSG The studied BSSG is composed of three separate brushless synchronous machines SM mounted on the same shaft [7] as shown is Fig.1: a permanent magnet generator 4003

(PMG), an exciter machine which is a synchronous machine with a fixed excitation (stator) and rotating three-phase windings (rotor) and a main starter/generator (MSG) constituted of a wound-rotor synchronous machine. The last two are interconnected via a rotating diode rectifier. When the starter/generator is operating in a motor mode, it must produce a starting torque that is significantly higher than the load torque in order to start the main engine. In the starting mode, the PMG does not interfere in the power chain, in opposition to the generation mode, where the PMG delivers the excitation to the exciter. Instead, the exciter stator is fed with AC voltage that induces, via a transformer effect an electromagnetic field in the exciter armature, whether the exciter rotor is rotating or at standstill. This electromagnetic field induces AC currents in the stator armature of the exciter, which in turn are rectified by the rotating rectifier and supplied to the rotor of the main starter/generator. Variable frequency AC power is supplied from the control device to the main starter/generator stator. This AC power produces a rotating magnetic field in the main stator leading the main rotor to rotate and to supply mechanical output power. As for the generation operation of this machine, it is described in [8].

Vdh, Vqh, Idh and Iqh are the high frequency components of dand q-axis voltages and currents. Rdh, Rqh, Ldh and Lqh are the d- and q-axis resistances and inductances at high frequency. In the (α,β) frame, where a rotating high frequency voltage is injected, and defined as : ⎡Vαh ⎤ ⎡cos(ω h .t )⎤ ⎢V ⎥ = Vh .⎢ ⎥ ⎣ sin(ωh .t )⎦ ⎣ βh ⎦

the system (1) can be described by: ⎡Vαh ⎤ ⎡Ζ ddh ⎢V ⎥ = ⎢ Z ⎣ βh ⎦ ⎣ dqh

c

Vd

The equivalent circuit of the main starter/generator in the high frequency domain is represented in Fig. 2 [7].

VSI 3Φ

Lddh

Iαh

Vex

Va_p

Rqqh

Vb If

Vrc_ex

Vra_ex

Zqqh

Vβh

Vrb_ex

Exciter

Lqqh

Iβh

Vf

S

PMG

Rectifier

Zdqh.Iβh

Zddh

Va

Vc Iex

Vb_p Rotating Parts N

(3)

⎛ R + R + jωh.(Ldh + Lqh) ⎞ ⎛ Rdh − Rdh + jωh.(Ldh − Lqh) ⎞ ⎟⎟ + ⎜⎜ ⎟⎟.cos(2θ ) Zddh = ⎜⎜ dh dh 2 2 ⎝ ⎠ ⎝ ⎠ ⎛ Rdh + Rdh + jωh.(Ldh + Lqh) ⎞ ⎛ Rdh + Rdh − jωh.(Ldh + Lqh) ⎞ Zqqh = ⎜⎜ ⎟⎟ + ⎜⎜ ⎟⎟.cos(2θ) 2 2 ⎝ ⎠ ⎝ ⎠ ⎛ Rdh + Rdh − jωh .( Ldh + Lqh ) ⎞ (4) ⎟⎟. sin(2θ ) Z dqh = ⎜⎜ 2 ⎝ ⎠

Vαh Vc_p

Z dqh ⎤ ⎡ I αh ⎤ . Ζ qqh ⎥⎦ ⎢⎣ I βh ⎥⎦

With

Rddh VSI 1Φ

Vd

(2)

Zdqh.Iαh

Main S/G

Fig. 2: Machine model at high frequency in the (α, β) frame

Fig.1: Brushless synchronous starter generator schematic

III. PRINCIPLE OF HIGH FREQUENCY INJECTION In this section, the principle of the HF injection together with the synchronous frame that is developed to estimate the rotor position is explained. A. Model of the BSSG at high frequency When a high frequency signal is injected in the main starter/generator, the back-emf voltage and the coupling terms are neglected at standstill and low speed. Therefore, the MSG can be written when considering only the stator components as [9]:

0 ⎤ ⎡I dh ⎤ ⎡Vdh ⎤ ⎡Rdh + Ldh.s . ⎢V ⎥ = ⎢ 0 Rqh + Lqh.s⎥⎦ ⎢⎣I qh ⎥⎦ ⎣ qh ⎦ ⎣

(1)

The current in the (α, β) frame can be expressed after some trigonometric simplifications as in [10-11]: ⎡ Iαh ⎤ ⎡ Iαp . cos (ωh .t − ϕ p )⎤ ⎡ Iαn . cos (2θ − ωh .t + ϕ n )⎤ ⎥+⎢ ⎢ ⎥=⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎢ ⎥ ⎢⎣ I βh ⎥⎦ ⎢⎣ I βp sin (ωh .t − ϕ p ) ⎥⎦ ⎢⎣ I βn sin (2θ − ωh .t + ϕ n ) ⎥⎦ ⎡ I αh ⎤ ⎢ ⎥ = Vh ⎢ ⎥ Z p ⎢⎣ I βh ⎥⎦

⎡cos (ω h .t − ϕ p )⎤ ⎡cos (2θ − ω h .t + ϕ n )⎤ ⎥ + Vh .⎢ ⎥ .⎢ ⎢ ⎥ Zn ⎢ ⎥ ⎢⎣ sin (ω h .t − ϕ p )⎥⎦ ⎣ sin (2θ − ω h .t + ϕ n )⎦

where: I αp = I βp =

Vh Ζp

and

I αn = I β n =

Vh Ζn

knowing that Zn and Zp can be approximated to:

4004

(5)

(6)

Ζp = Ζn =

2.Ldh .Lqh Ldh + Lqh 2.Ldh .Lqh Ldh − Lqh

.ω h

(7)

.ω h

Therefore, injecting a high frequency signal in the machine results in two components of the current carrier signal that are the positive and negative sequences. The positive sequence component doesn't contain any spatial information about the rotor position and is proportional to the average stator inductance. Yet, it is the negative sequence component that contains spatial information in its phase about double rotor position. The negative sequence component amplitude depends on the saliency level of the machine [12], on the amplitude of the injected HF signal as well as the chosen frequency. B. Synchronous frame filtering When operating in the start-up mode, the fundamental current is added to eq. (5) as below: ⎡Iαh ⎤ ⎡Iα1.cos(ω.t)⎤ ⎡Iαp.cos(ωh.t −ϕp )⎤ ⎡Iαn.cos(2θ −ωh.t +ϕn )⎤ ⎥ +.⎢ ⎢ ⎥ = .⎢ ⎥ +.⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢⎣Iβh ⎥⎦ ⎢⎣ Iβ1 sin(ω.t) ⎥⎦ ⎢⎣ Iβp sin(ωh.t −ϕp ) ⎥⎦ ⎢⎣ Iβn sin(2θ −ωh.t +ϕn ) ⎥⎦

(5)

The synchronous frame filtering is needed for two purposes: 1- Filtering the fundamental current in order to ensure the current regulation without any perturbation caused by the HF signal injection. 2- Extracting the spatial information contained in the phase of the negative-sequence carrier signal current and delivering it to the observer. The implemented scheme proposes to filter off the positive sequence carrier signal current by using high pass filters (HP1 and HP2) implemented in two different reference frames respectively (hp-frame and hn-frame) [10]. This is achieved by applying different rotations. On the other side, the position information is extracted by using a low pass filter LP1 applied in a reference frame hn2-frame as shown in Fig. 3.

high control quality. Furthermore, the generic structure of the developed modules allows producing controllers in large quantities, thus reducing the cost of the development. Moreover, the DO-254 (Design Assurance Guidance for Airborne Electronic Hardware), a standard adopted by the Federal Aviation Administration (FAA) for electronics intended for flight use, was developed and many FPGAs firms offer solutions easing verification with DO-254 compliance. All these reasons helped choosing the FPGA as a target for the implementation the sensorless algorithms developed to start the main engine. Among the different firms, it is the Actel Proasic A3P1000 that is used. This is a Flash-based FPGA that gives the advantage of being a secure, low-power, single-chip solution. More importantly, it is the most useful technology in aircraft and space systems since it guaranties the configuration against the SEU (Single Event Upset) radiations [14]. Nevertheless, the development and optimization of the consumed resources over the FPGAs need a special care from the designer. By following the methodology presented in [1516], the design of such complex structures becomes easier. A. The FPGA architecture Fig. 4 presents the VHDL architecture of the HF injection estimation controller. It represents the lowest branch of Fig.3. HP1 and HP1’ represent the high pass filters on (α, β) both axis; LP1 and LP1’ represent the low pass filters. The control unit ensures the control and the sequence order of the different integrated blocks. Start

Ia Ib Ic

Control unit of position estimation based on HF injection

a b

θˆ α

HP1

Rotation 1

β

HP1’

-ωh.t Clk_40 MHz

Rotation 2

LP1

PLL LP1’

2.ωh.t

Clk_synchro Gen_clk

HF injection estimation controller Fig. 4: VHDL architecture of the HF injection estimation controller

B. Time performances Fig. 3: Synchronous frame filtering

IV. FPGA IMPLEMENTATION FPGAs are becoming very popular in aeronautics industries due to their high performance computation, high sampling rate, reliability, cost and size [13]. With reconfigurable hardware it is also possible to apply flexibility to highly parallel functions allowing high-speed missions to be executed in a very short time with a large bandwidth and a

Table 1 represents the FPGA time/area performances of the carrier signal injection based sensorless control when using a FPGA Actel A3P1000 type with a clock of 40 MHz . Fig. 3 shows the corresponding timing diagram. The resultant calculation time TCT of the algorithm is then 2.575 μs . By adding the conversion time tAD, the total execution time of the algorithm is of 2.925 μs. This execution time is tiny compared to the sampling period (25 μs). This is particularly due to high computation capabilities of FPGAs. Consequently, in terms of estimation performances, a quasi-instantaneous estimation is ensured 4005

End

ωˆ

which enhances the estimation reactivity and bandwidth. Hence, the HF sensorless controller preserves its performances without any need for delay compensation nor additional modifications due to calculation time. Table I FPGA TIME/AREA PERFORMANCES OF THE HF INJECTION ALGORITHM

Module

Latency

AD Interface abc-αβ Rotation 1 HP1 HP1’ Rotation 2 LP1 LP1’ PLL

16 7 12 8 8 12 12 12 22

Computation time tAD = 0.4 μs tabcαβ= 0.175 μs tR1 = 0.3 μs tHP1 = 0.2 μs tHP1’ = 0.2 μs tR5= 0.3 μs tLP1 = 0.3 μs tLP1’ = 0.3 μs tPLL = 0.55 μs

TCT = tabcαβ+tR1+tHP1+tHP1’+tR2+tLP1+tLP1’+tPLL Execution time Tex=tAD+TCT Number of Consumed core cells resources Block rams Multipliers (16x16) Multipliers (23x23)

TCT= 2.525 µs

BSSG

Tex = 2.925 µs 24332 out of 24576 (99%) 6 out of 32 2 1

Fig. 6: Synoptic of the used testbench

It is important to note that the execution of HP1 and HP1' together with LP1 and LP1' could have been launched simultaneously if only there had been enough FPGA resources. In this case, the execution time could have been Tex = 2.425 µs. Actually, the parallelism feature of the FPGA was sacrificed because of lack of FPGA resources (99% of the resources). Ts Start

Tex_HF tAD

Ts

TCT

tk

tAD tk+Tex_HF

TCT

tk+1

Sample Estimation of Sample I(a,b,c) [k] the position θˆ [k] I(a,b,c) [k+1]

tk+1+Tex_HF

t(s)

Estimation of the position θˆ [k]

Fig. 5: Timing diagram of the HF injection based controller

V.

EXPERIMENTAL RESULTS

Fig. 6: Actual testbench representation

The different used equipment such as:

The synoptic of the general structure of the developed testbench that is used for the validation of the carrier-signal injection-based sensorless control, as well as an actual representation are given in Fig. 5 and 6. The used machine for the validation of the different tests is a 40 kVA BSSG.

4006

ƒ

the machine specifications that is operating in high frequency range and in the saturation mode, (the parameter of the machine are given in Appendix )

ƒ

the used inverter with its different protection functions and IGBTs working at high sampling frequency (20 kHz ),

ƒ

the choice of the hardware solutions that is FPGA, in order to process the different algorithm at high sampling frequency in a low execution time,

ƒ

the choice of the FPGA target that is the ACTEL FPGA, due to its immunity towards the SEU,

ƒ

the methodology of VHDL implementation of the sensorless algorithms that is mandatory to follow for certification issues [16], were selected since they meet the requirements of an aeronautics testbench. Different tests are elaborated on the used BSSG and the results were logged and presented hereafter.

(a)

Fig. 8-(a): α-β plot of the stator currents, (b): α-β plot of negative sequence currents C.

A. Experimental spectrum analysis of the current Before testing the sensorless technique based on the HF injection, it is interesting to identify experimentally the spectrum of the currents when a HF signal is injected which has a frequency of 2 kHz in this work.

(b)

Experimental results at start-up of the machine

Figure 8 shows the actual and estimated positions together with the current of phase A Ia during the start-up when using the carrier-signal-injection-based self-sensing. The injected signal has a frequency of 2 kHz. It can be seen that good position estimation accuracy is obtained.

180° 400 ms

50A 400 ms

Fig. 8: Actual position, estimated position and Ia during start-up

D. Experimental results at fixed speed. In this test, the machine speed is constant at 600 rpm (20 Hz). The estimated and actual positions are presented in Fig. 9. Fig. 7: Spectrum analysis of the currents with HF injection at 2 KHz at different speeds.

In this case, the machine's impedances are those of high frequency. The machine is driven at different speeds. Two main harmonics were detected in the spectrum of the current that correspond to the positive sequence harmonic and the negative sequence harmonic. Fig. 7 shows the obtained current spectrum for different speeds. It can easily be noticed the positive sequence is present at 2 kHz while the negative sequence harmonic varies with the rotational speed of the machine. B. α- β plot of the currents Fig. 8-(a) depicts the α-β plot of stator currents where the modulation created by the HF signal injection is shown. Figure 8-(b) shows the α-β plot of negative sequence currents. It can be seen that the α-β plot is not circular and this is due to the saliency of the machine.

180° 40 ms

Fig. 9: Estimated and actual positions at to 600 rpm

When using the carrier-signal injection based self-sensing with the BSSG, the obtained estimation error varies between ± 15° as shown in Fig. 10. 4007

APPENDIX MAIN STARTER GENERATOR PARAMETERS 40 KVA, 55V, 400 Hz, 3 Phases, Y connection, 2 pole pairs Stator resistance Rotor resistance Rs = 12 m• Rr = 0.34 • d axis stator inductance Mutual inductance Ld = 0.6 H Msf = 13.151 mH q axis stator inductance Nominal stator current Lq = 0.3 H Isn = 290 A

30° 40 ms

REFERENCES [1]

Fig. 10: Position estimation error at 600 rpm E. Experimental results at standstill In this test, the rotor is blocked and the HF signal of 2 kHz is injected at the stator terminals of the machine. Then, the rotor is manually rotated and the actual and estimated positions are logged at different rotor positions. Fig. 11 shows the obtained results at standstill. It can be seen that good position estimation accuracy is obtained. 72°

[2] [3]

[4]

[5] [6]

1s [7]

[8]

[9]

Figure 11: Actual and estimated positions for different positions of the rotor of the machine [10]

VI.

CONCLUSION

In this paper, the carrier signal based sensorless controller is developed to estimate the rotor position of a brushless synchronous starter/generator from standstill up to nearly 5% of the rated speed (i.e. 600 rpm, rated speed 12000 rpm). This technique is implemented on an FPGA target and is validated with a 40 kVA BSSG. The execution time of this method is less than 3µs, proving that no phase lag is introduced due to the execution time. The rotating carrier signal based sensorless controller delivers position estimate at standstill and low speed and good estimation accuracy is attained (estimation error of ± 15°). Therefore, the sensorless control for an aircraft use as it is described in this paper, can be the solution for a more reliable aircraft. However, these promising results need to be further enhanced in order to fully meet the requirements of the aircraft manufacturers in order to be able to apply the sensorless control in the start-up of the engine of the more electric aircraft.

[11]

[12]

[13] [14] [15]

[16]

4008

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