Biomechanical Energy Harvesting

www.sciencemag.org/cgi/content/full/319/5864/807/DC1

Supporting Online Material for

Biomechanical Energy Harvesting:

Generating Electricity During Walking with Minimal User Effort

J. M. Donelan,* Q. Li, V. Naing, J. A. Hoffer, D. J. Weber, A. D. Kuo

*To whom correspondence should be addressed. E-mail: [email protected]

Published 8 February 2008, Science 319, 807 (2008)

DOI: 10.1126/science.1149860

This PDF file includes:

Materials and Methods Figs. S1 to S3 Table S1 References

Other Supporting Online Material for this manuscript includes the following: (available at www.sciencemag.org/cgi/content/full/319/5864/807/DC1)

Movies S1 to S4

Supporting online material Biomechanical energy harvesting

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Materials and Methods The energy harvesting device includes subsystems for mechanical power transmission, electrical power generation and control (Figure 2). The transmission system comprises a gear train that transfers low velocity and high torque at the knee into the high velocity and low torque required for efficient power generation. It also includes a roller clutch (S99NH3MURC1616, SDP/SI, New York) that only engages the transmission during knee extension and rolls freely around the input shaft during knee flexion. Electrical power generation is performed by a miniature three-phase brushless rotary magnetic generator (EC45 Flat, Maxon, Burlingame, CA) with a small terminal resistance, to minimize internal power dissipation, and a low speed constant, to minimize the required gear ratio. The generator output is directed to a computer-controlled, low-latency relay switch (PhotoMOS relay AQZ202, Panasonic, NJ) that can be opened to prevent electricity generation, and closed to direct the power to off-board load resistors. Knee angle is measured using a potentiometer (6639S-1-502, Bourns Inc., CA) mounted on the input shaft. A CNC-manufactured aluminium chassis houses the transmission and generator. The chassis (0.76 kg) is mounted on a orthopaedic knee brace (0.89 kg, GII Trainer; Ossur, Reykjavik) modified to accommodate device components. Thigh and shank extensions were added to more tightly couple knee motion to brace hinge motion. Given the generator terminal resistance and speed constant, there is an optimal combination of gear ratio and output resistance to maximize the electrical power output, maximize the mechanical to electrical efficiency and produce a reaction torque equivalent to the joint torque normally produced by muscles at the end of the swing phase during moderate speed walking. For example, the torque applied to the knee can be increased by increasing the gear ratio or decreasing the output resistance with the former resulting in increased frictional losses and the later resulting in a greater fraction of electrical power dissipated by the generator. In these experiments, we used the gear ratio (113:1) and output resistance (5 ohms) predicted to be optimal using computer simulations that modelled friction of the transmission but not the inertia of the transmission and generator. While the actual optimal parameters are likely to be subject- and speed-specific, iterative human trials demonstrated that the chosen parameters worked well for all subjects. We operated the device in three modes. In the disengaged mode, the roller clutch was mechanically disconnected, decoupling the rest of the system entirely. This mode served as a control condition for the human subject experiments to account for any physiological changes that resulted from carrying the added mass independent of physiological changes resulting from energy harvesting. The brace arm and input shaft inertia as well as hinge joint friction were still present but the net torque required to overcome these effects was quite small. In the continuous generation mode, the relay switch was kept closed, so that power generation occurred during the entire knee extension phase. In the generative braking mode a control system selectively engaged and disengaged the relay switch to target the end of walking’s swing phase. In the latter two modes, the transmission and generator always provided some resistance to knee extension, even when power was not being generated (Figure 1). The beginning of swing phase knee extension was determined using the sensed knee angle and its time derivative. To engage power generation in the middle of knee extension, which is approximately when knee flexor muscles become active, switch closing was delayed by 70-90 ms. The control system detected the onset of stance phase knee flexion and then opened the switch after a delay of 80 ms. This disengagement delay


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allowed the generator to finish harvesting the kinetic energy that remained in the transmission and generator inertia from the swing phase motion while avoiding power generation from knee extension later in stance. Power generation during this stance knee extension phase likely increases the positive mechanical work required by muscle and thus metabolic cost. The control system was coded in Simulink, compiled using Real Time Workshop and executed at 1 kHz using Real Time Windows Target on a desktop computer (Mathworks, Natick, MA). Communication between the computer and device occurred through the umbilical cable and an A/D and D/A board (NI 6031E, National Instruments Inc, CA). This system also measured and recorded the voltage drop across the resistors, and thus the electrical power being generated. While we have focused on harvesting energy from knee motion at the end of walking’s swing phase, power generation is possible from other periods of the gait cycle. At the beginning of the stance phase, for example, the knee flexes while the knee extensor muscles generate an extensor torque performing substantial negative work to aid in the redirection of the centre of mass velocity (1, 2). At moderate walking speeds, the amount of available energy is approximately equal to that at the end of swing and it increases strongly with speed (3). Our current device was initially designed to target this region in addition to the end of swing. To accomplish this, we used two oppositely-oriented roller clutches on the input shaft and an extra stage of gearing for knee flexion. This caused the generator to spin in the same direction regardless of the direction of knee motion and increased the gear ratio during flexion. Although the higher gear ratio was required to better match the low angular velocity and high torque characteristics of the early stance mechanical power, it had a major drawback. Despite the fact that the control system opened the power generation circuit during early swing, the high knee flexion angular velocity resulted in awkwardly large resistive forces due to transmission and generator inertia. This was not a problem for knee extension where power generation was engaged during the late swing when knee angular velocity is high and disengaged during late stance when knee angular velocity is low. While this drawback forced us to disregard early stance power generation in this device generation, future energy harvesting devices could double power generation should a suitable mechanism for disengaging the transmission be found. To evaluate the efficiency of converting mechanical to electrical power, we designed a test ergometer to drive the device with a specified kinematic profile using a servo-motor while measuring the angular velocity, reaction torque and electrical power generation (Figure S1). The kinematic profile was the average knee angle used across our human subject trials replicated for eight stride cycles. The device was first tested in the disengaged mode to determine the torque required to overcome the test ergometer gravitational and inertial forces. This torque was subsequently subtracted from all other torque measurements. Mechanical power was calculated as the product of angular velocity and the remaining torque. The device efficiency was calculated as the ratio of the output electrical energy to the input mechanical work where energy and work were calculated by integrating electrical and mechanical power, respectively, over the eight simulated stride cycles. The continuous generation mode converted mechanical power to electrical power with a device efficiency of 63% with the remaining power being dissipated as heat due to gear friction and electrical resistance within the generator. The device efficiency when operating in the generative braking mode was 56%. The efficiency is smaller because the device spent a greater amount of time dissipating mechanical energy without producing electrical power. To determine the sensitivity of the calculated efficiencies to the knee kinematics, we


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scaled the input angular velocity profile by ±10% and measured only small changes in efficiency (<3%). We tested our hypotheses on six male subjects treadmill walking at 1.5 m/s. All subjects (body mass 78.3 kg ± 12.4; mean ± s. d.) were healthy and exhibited no clinical gait abnormalities. Before the experiments began, volunteers gave their informed consent to participate in accordance with university policy. We then determined each subject’s resting metabolic rate while standing by measuring oxygen consumption and carbon dioxide production using open circuit respirometry (Vmax Sensormedics, Yorba Linda, CA). Next, subjects completed a 10 min normal walking trial to determine the incremental cost of wearing the device and familiarize subjects with treadmill walking. This was followed by three randomly ordered walking trials, corresponding to each of the three device modes. Subjects wore a device on each leg. The trials were 20 min in duration. The trial duration appeared to be sufficient for each subject to settle in to a preferred pattern of walking for each mode as we found no significant differences in the stride frequency and knee kinematics between the 10th minute and the 20th minute. Furthermore, the first three subjects repeated the experiment on three different days within the same week and we found no changes in gait between days. We measured the average rates of oxygen consumption and carbon dioxide production over the last five minutes of each trial, and calculated metabolic cost using a standard equation (4, 5). We subtracted the metabolic cost for standing from all walking values (3). Average electrical power generation was calculated by integrating the instantaneous electrical power over the complete stride cycle and then dividing by stride time. Statistical tests were applied as follows. Jarque-Bera tests (6) were performed to determine whether the data could be approximated with a normal distribution. These failed to reject the normal distribution (P = 0.77 for braking generation, for P = 0.99 for continuous generation). These were therefore followed by two-sided t-tests. These included t-tests comparing the COH for continuous and braking generation modes against the value of 6.35 expected for conventional generation, and a paired t-test evaluating the difference between these two modes. To provide insight regarding the effect of energy harvesting on normal walking kinematics, we compared our knee angle results with data available from the literature (7). In either power generation mode, subjects used the normal pattern of swing flexion followed by swing extension and stance flexion followed by stance extension (Figure S2), both qualitatively similar to normal walking (see supporting videos). There were, however, some measurable differences compared to normal kinematics. In particular, the knee extended more slowly at the end of swing when wearing the device resulting in a more flexed posture at the beginning of stance. The degree of stance phase flexion was approximately the same as during normal walking but the knee extended more quickly during stance phase extension resulting in relatively equal kinematics by the end of stance. The kinematic differences at the end of swing suggest that the sum of the knee flexor torques provided by the knee flexor muscles and the device is greater than when the device is absent. The net flexor torque could be reduced by decreasing the flexor torque provided by the device with consequent reductions in generated power. It is also possible that net flexor torque could be reduced with more training as subjects learn to further decrease their knee flexor activity. While studying the differences in kinematics between conditions is useful for understanding the effects of energy harvesting on walking biomechanics, it should not be


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assumed that the kinematics of walking without wearing the device are the optimal kinematics for walking while wearing the device. For most uses, the differences in metabolic cost and electrical power generation are more important than slight changes to walking kinematics. To estimate the electrical power generation capabilities of our energy harvesting technology, we had a single subject perform a range of conditions on a second day of experiments. For comparison with the subject averages, this 90.9 kg subject generated 8.2 W electrical when walking at 1.5 m/s in the engaged-clutch mode (Figure S3). When walking speed was increased to 2.0 m/s, the subject’s power generation increased to 12.6 W electrical. Walking at 1.0 m/s, a speed which is slower than typically preferred, power generation was 6.3 W electrical. Uphill and downhill walking tended to decrease and increase the power generation, respectively. When the subject switched to a relatively slow run, 2.5 m/s, power generation jumped to 20.4 W electrical. The maximum power that this subject could generate was 54.0 W electrical accomplished during a short duration seated leg extension task.


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References and Notes 1. J. M. Donelan, R. Kram, A. D. Kuo, Journal of Biomechanics 35, 117 (Jan, 2002). 2. D. A. Winter, Biomechanics and motor control of human movement. (Wiley, New York, ed.

2nd, 1990), pp. xvi, 277. 3. J. M. Donelan, R. Kram, A. D. Kuo, J Exp Biol 205, 3717 (Dec, 2002). 4. P. G. Adamczyk, S. H. Collins, A. D. Kuo, Journal of Experimental Biology 209, 3953 (Oct

15, 2006). 5. J. M. Brockway, Human Nutrition. Clinical Nutrition 41, 463 (Nov, 1987). 6. A. K. Bera, M. J. Carlos, Economics Letters 6, 255 (198). 7. J. Rose, J. G. Gamble, Human walking. (Williams & Wilkins, Baltimore, ed. 2nd, 1994), pp.

xvii, 263.


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No Device Disengaged Generative Braking Continuous Generation

Subject

Metabolic

Power (Watts)

Metabolic

Power (Watts)

Metabolic

Power (Watts)

Metabolic Power

(∆Watts)

Electrical Power (Watts)

Cost of Harvesting

(dimensionless)

Metabolic Power (Watts)

Metabolic Power

(∆Watts)

Electrical Power (Watts)

Cost of Harvesting

(dimensionless)

1 359 432 405 -27 4.1 -6.5 417 -15 6.9 -2.1

2 261 325 319 -6 5.0 -1.2 344 19 6.7 2.8

3 322 373 375 2 4.7 0.5 390 17 6.7 2.6

4 199 262 268 6 3.6 1.7 265 4 6.0 0.6

5 355 411 435 23 6.0 3.9 434 22 7.3 3.1

6 348 396 426 31 5.1 6.0 453 58 8.2 7.1

MEAN 307 366 371 5 4.8 0.7 384 18 7.0 2.3

STD 64 63 66 21 0.8 4.4 70 24 0.7 3.0

SEM 26 26 27 8 0.3 1.8 28 10 0.3 1.2

Table S1. Metabolic power, electrical power and cost of harvesting results for our six individual subjects. The Metabolic Power (∆Watts) columns are the difference in metabolic cost between each of the power generation modes and the Disengaged mode. The Disengaged condition served as the control condition because it accounts for the metabolic cost of carrying the mass but not the metabolic cost of generating electricity. For comparison with normal walking, the No Device condition presents the cost of walking without wearing the device. The calculated values for the mean (MEAN), standard deviation (STD) and standard error of the means (SEM) are presented in the bottom three rows, respectively. Note that average cost of harvesting yields different values than the ratio of the average difference in metabolic power to the average electrical power.


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Figures

Figure S1. An illustration of the test ergometer used in this study.


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Continuous gene rationGenerative braking

Normal Walking120

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Figure S2. Comparison of knee kinematics during normal walking and walking while wearing the device. For the continuous generation (red) and generative braking (blue) results, knee angle was measured using the onboard potentiometer. For each subject, the last one minute of stride cycles were averaged for the right and left legs and then the average individual leg results were then averaged. The solid lines represent the average values between the subjects and the shaded areas represent the between-subject variability using one standard deviation on either side of the mean. The normal walking data (green) was taken from the literature (7).


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0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

0 0.5 1.0 1.5 2.0 2.5 3.0

0 0.5 1.0 1.5 2.0 2.5

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Figure S3. Electrical power generated by a single subject walking at (A) 1.0 m/s, (B), 1.5 m/s and (C) 2.0 m/s. The devices are operating in the continuous generation mode with an output resistance of 3 ohms. The green and red lines are the power generated by the devices worn on the right and left legs, respectively. The time-varying lines are the instantaneous power and the horizontal lines are the average power—when only one line is visible, the right and left legs had equal power generation. The horizontal grey line is the total power from both legs. Three stride complete stride cycles are shown beginning with right leg swing initiation.

SOM Movie Captions Movie S1: Generative Braking - In this mode, we programmed the harvester to engage only during the end of the swing phase, producing electrical power while simultaneously assisting the knee flexor muscles in decelerating the knee. The mask and mouthpiece measure the metabolic cost. We use the cabling and computer to engage and disengage power generation and for quantifying the amount of generated power. Movie S2: Continuous Generation - In this mode, the device harvests energy whenever the knee is extending irrespective of whether or not the knee is accelerating or decelerating. Movie S3: Disengaged - In this mode, we decoupled the gear train and generator from knee motion. It served as a control condition to estimate the metabolic cost of carrying the harvester mass, independent of the cost of generating electricity. Movie S4: Normal Walking - Comparing this movie to the other movies illustrates that walking with and without wearing the device is qualitatively similar.

Biomechanical Energy Harvesting

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