A Control Method for Power-Assist Devices using a BLDC Motor for Manual Wheelchairs

Abstract

This paper proposes a new operation and control strategy for Power-Assisted Wheelchairs (PAW) using one brushless DC (BLDC) motor. The conventional electrical wheelchairs are too heavy and large for one person to move because they have two electric motor wheels. On the other hand, the proposed PAW system has a small volume and is easy to move due to the presence of a single wheel motor. Unlike the conventional electric wheelchairs, this structure for a PAW does not have a control joystick to reduce its weight and volume. To control the wheelchair without a joystick, a special control system and algorithm are needed for proper operation of the wheelchair. In the proposed PAW system uses only one sensor to detect the acceleration and direction of PAW's movement. By using this sensor, speed control can be achieved. With a speed control system, there are three kinds of operations that can be done on the speed of a PAW: the increment of PAW speed by summing external force, the decrement of PAW speed by subtracting external force, and emergency breaking by evaluating the time duration of external force. The validity of the proposed algorithm is verified through experimental results.

I. INTRODUCTION

In recent years, elderly and disabled people have become more active in social activities due in part to the development of medical and electric technology. The areas of activity for these people are wider than they were a decade ago. Electric wheelchairs are usually used for short distance movement while cars are required for the movement of electric wheelchairs over a long distance. However, conventional wheelchairs which have joysticks are too heavy and large to load into a car alone. Some PAWs have been developed to achieve light weight and portability from manual wheelchair [1]-[9]. These PAWs are not equiped with joysticks and use torque sensors or acceleration sensors to measure or estimate the speed or acceleration which is generated by the pushing power of the user. Pushing power is used for the propulsion of manual wheelchairs. For the most part, there are two types of PAW systems. One is the systems having two motors connected with both wheels of the wheelchair. In this type of PAW, since the PAW is already installed on the wheelchair, there is no need for the user to install it. However, it is difficult to repair once it is damaged. The second type is the attachable power assist device (PAD), where attachable and portable hardware is attached to a wheelchair whenever the user wants to use the PWA system. Attachable PADs can be simply applied to several manual wheelchairs.

The conventional studies on PAWs focused on the use of two motors. These PAW systems use pushing power to generate the assist power. Because assist power is temporarily added for propulsion, a number of propulsion motions (pushing wheels) are required to continuously move the wheelchair. However, excessive propulsion motions have a bad effect on wrist joints [10]. In addition, the installation of two motors causes a weight increment. Therefore, the user needs considerable force to load or unload a wheelchair into or out of a car.

In this paper, a different control algorithm is proposed and compared to the conventional PAW control algorithm. The concept of the proposed algorithm is that the wheelchair can maintain speed for a long time with a single pushing action. It helps the user move a long way without applying a lot of pushing actions. This proposed control algorithm uses one acceleration sensor. The control algorithm is composed of three control methods. One is the accumulation of the speed command to increase the speed of the wheelchair. The second method is the deceleration of the speed command to decrease speed of the wheelchair. The third is the quick stop control for emergency situations. These algorithms are based on the output of the acceleration sensor and are combined for speed control. The proposed algorithm is verified by experimental results.

 

II. MODELING OF THE PROPOSED PAW WHEELCHAIR

A. Conventional Model of a Wheelchair Controlled by Two Wheels [11]

Fig. 1 shows the conventional model of a wheelchair. The wheel chair model has two domains which are the propulsion and rotation, where v is the propulsion speed, and ω is the rotational speed. The kinematics of the wheelchair can be represented as (1) and (2).

where are the angular speeds of the left and right wheels, ϕ is the moving direction, R is the radius of the wheel, and W is the distance between the two wheels.

Fig. 1.Electrical wheelchair model.

Then, the time derivative of (1) and (2) can be represented as follows.

The propulsion force and rotation torque of the wheelchair can be expressed as (5) and (6).

To derive the motion equation of the wheelchair, the total kinetic energy of the wheelchair L is given by equation (7).

Solving the Lagrange equation, the load torque equation of the wheelchair can be presented as (8).

where, m and J are the mass and inertia of the wheelchair, and Jω and Bω are the inertia and friction coefficient of the wheel, respectively.

B. Model of the Proposed PAW Wheelchair

Fig. 2. shows the proposed model using one propulsion motor. In this case, the motor can control only the propulsion force. That means the rotational force can be neglected, that is θl and θr are equal. The kinematics of the proposed wheelchair can be represented as (9) and (10).

where, are the angular speed and acceleration speed of the propulsion motor.

Fig. 2.Proposed PAW wheelchair model.

The propulsion force is replaced by (11), and the total kinetic energy of the proposed wheelchair L is given by equation (12).

Finally, the load torque equation of the proposed wheelchair can be derived as (13).

 

III. PROPOSED POWER ASSIST DEVICE CONTROL ALGORITHM

A. Maximum Speed Tracking and Keeping Algorithm

In the proposed PAW, an acceleration sensor is used to detect the external force applied by the user. The output of the acceleration sensor is converted to the additional speed, vh , which is used for the generation of the speed command of the proposed PAW system.

The acceleration sensor has a positive value when the user pushes the wheelchair wheels in the positive direction as shown in Fig. 3. Fig. 3 shows the direction of the additional speed and acceleration when a positive direction external force is applied, where ah is the acceleration measured by the acceleration sensor, and vh is the additional speed produced by an external force. vh can be calculated by integrating the acceleration as given by equation (14).

Fig. 3.Movement of Power-Assisted Wheelchair.

This additional speed can be added to or subtracted from the real wheelchair speed, v .

Fig. 4 shows the profile of ah and vh. When the user pushes the wheelchair wheels, ah can be measured through the acceleration sensor. Following the profile of ah, the real velocity of the wheelchair increases. However, the speed of the wheelchair steadily decrease due to frictional force. The external force makes the additional speed profile vh like the half cycle of a sine waveform. From the profile, assisted-speed va can be generated from vh by using equation (15). It is not suitable to adapt vh as a speed command from the acceleration sensor output since it has a lot of noise and a small magnitude. Thus, the scale and slope of va can be controlled by using equation (15).

where, va is the assisted-speed, Ka is the assistance coefficient, and τa is the time constant.

Fig. 4.Profile of acceleration sensor and detecting maximum speed to keep constant speed for PAW.

To drive continuously by applying only one propulsion motion, the maximum value is retained for the calculation of the speed command. The speed command can be acquired by using the differential value of va to detect the maximum speed value. Fig. 4 schematically shows the above mentioned explanations of the mechanism used to detect the maximum speed point. According to the differential value of va , the speed command can be presented like equation (16)

where va_old is the value of va calculated before a period of time.

B. Algorithm for Increasing the Speed Command

In the proposed PAW system, the speed of the wheelchair can be changed according to the magnitude and direction of the external force. Therefore, the speed command can be determined by summing the number of the external forces according to the drive direction as va1 , va2 , va3 and va4 which are determined by each external force as shown in Fig. 5. This means that whenever an external positive force is applied, the speed command increases to the next level as depicted in Fig. 5.

Fig. 5.Summation of speed by adding the external force.

C. Braking Algorithm

A braking algorithm must be included in the proposed system unlike conventional electric wheelchairs with a joystick or PAW based torque controls. There are two steps in the proposed braking algorithm.

Firstly, the brake ratio is decided according to the time duration. Then, the braking method is decided since there are two braking methods. One is the deceleration in case of a decrement in the speed command following the decided brake ratio. Another is a quick stop if the user wants to reduce the speed command quickly.

The braking motion is activated by grasping the wheelchair wheel. In this case, the profile time of the deceleration is the reference signal of the braking as shown in Fig. 6 and Fig. 7, respectively.

Fig. 6.The velocity and acceleration during deceleration/stop.

Fig. 7.Acceleration during reduction of speed.

Fig. 6 shows the direction of the additional speed and the acceleration of the wheelchair during the braking operation. The acceleration has a negative value in accordance with the driving direction.

Fig. 7 shows the acceleration pattern in case of the braking operation of the wheelchair. To avoid the effects of noise, the brake signal is recognized after a few seconds from the point where grasping of the wheel occurs.

In Fig. 7, t1 is the point where grasping the wheelchair wheels for braking occurs. It is decided that the acceleration signal goes down under zero. t2 is the point of distinction for brake mode: speed decrement or complete break. The distinction is made up with the speed error and acceleration signal. If the user grips the rim strongly, the speed error reaches the distinction point in a short time. Otherwise, if the user grips the rim smoothly and continuously, the speed error gently increases to the distinction point over a long time. The distinction time is experimentally defined to be 15% of the speed commands. Thus, Tbr is the detection time between t1 and t2 and it is related to the brake ratio. The brake ratio determines the decremental ratio of the speed command. If Tbr is short, it means that the user wants to quickly reduce the speed command.

Fig. 8 shows the speed command according to Tbr and the brake ratio. The variables α is used for the division of Tbr . If Tbr has an arbitrary value between 0 and α, as in Fig. 8(a), it can be considered that the user wants to stop quickly. In this case, the brake ratio is determined to be a large value. If Tbr is longer than α, as shown in Fig. 8(b), the brake ratio is determined to have a small value and α is set by the acceleration profile.

Fig. 8.Speed command according to the brake ratio. (a) Large brake ratio. (b) Small brake ratio.

After the brake ratio is determined, Tstop is used for selecting the deceleration or quick stop of the wheelchair. Tstop is the elapsed time between t2 and t3 . If the user grasps the wheel for a moment, the speed is reduced for a short time and the speed again follows the speed command.

In this case, the acceleration acquires negative value for a moment. However, if the user grasps the wheel for a long time, the speed of the wheelchair is reduced continuously. In this case, the acceleration has negative value for a long time. If Tstop is longer than β, the system will decide to quick stop the wheelchair. Otherwise, it can be considered to be a deceleration of the speed command.

The deceleration operation is implemented in stages like the increasing operation of the speed command. As shown in Fig 9(a), the speed command is reduced in stages during the deceleration operation. The quick stop operation is used for quick stops in case of an emergency. Once the brake signal occurs, the first stage of deceleration is implemented. As shown in Fig. 9(b), the quick stop signal is generated during the first deceleration step.

Fig. 9.Speed command about two cases of brake.

 

IV. EXPERIMENTAL RESULTS

Fig. 10 shows a whole block diagram of the proposed algorithm. The proposed PAW system is composed of a DSP control system, a manual wheelchair and a PAW hardware system. The acceleration generated by an external force is used as the speed command for the DSP control system, and the system keeps the speed command steadily. If additional acceleration occurs during the speed control, the speed command increases in step. When the braking motion is detected, the brake-command ( Kbvb ) is subtracted from the speed command ( ). Then, the final speed-command ( v* ) is used as the reference speed for the DSP control system.

Fig. 10.Whole block diagram of the proposed control algorithm.

Fig. 11(a) shows the configuration of the wheelchair on which the power assist device is installed. Fig. 11(b) shows the backside of the wheelchair with the PAD. The power rating of the motor is 300(W).

Fig. 11.Configuration of wheelchair.

Fig. 12(a) shows a control board which uses a TMS320F335 as the main processor [12]. The acceleration sensor for the proposed algorithm is represented in Fig. 12(b). The sensor is a AM-3AXIS of STMicroelectronics [13] and experimental data are logged by a NI DAQPAD-6251.

Fig. 12.DSP control board and acceleration sensor. (a) DSP control board used for the experiment. (b) Acceleration sensor AM-3AXIS V03.

Fig. 13 and Fig. 14 show experimental results of the brake ratio according to Tbr . In the experiment, α is 0.5s. The Tbr counter counts every 100us. As shown in Fig. 13, the brake ratio is determined to have a large value when Tbr is shorter than 0.5s. As shown in Fig. 14, the brake ratio has a small value because Tbr is longer than 0.5s.

Fig. 13.Quick stop operation when Brake ratio = 0.01.

Fig. 14.Quick stop operation when Brake ratio = 0.005.

Fig. 15 shows experimental result of the continuous propulsion operation. To avoid malfunctions caused by noise, the propulsion motion is recognized when the output of the sensor is larger than a threshold value. In this experiment, the maximum speed is limited to 1.6m/s for the sake of safety, and the speed of each stage is 0.6 m/s. To track the speed command ( v* ), the current increases during the transient state, and the current is maintained at a fixed speed.

Fig. 15.Experimental results of the continuous increment of the speed.

Fig. 16 shows a waveform during the continuous deceleration operation of the wheelchair. To avoid malfunctions, the brake point is recognized when the acceleration is lower than the threshold. The current (i) increases during the deceleration operation. The reason is that a motion which grasps the wheelchair wheel is considered as an increase of the load condition until the controller recognizes the brake point.

Fig. 16.Experimental results of the continuous decrement of the speed.

Fig. 17 shows a waveform during quick the stop operation. In the experiment, the signal of the quick stop is generated when the acceleration ( ah ) has negative value for more than two seconds (β=2s) from the starting point of the first deceleration step. In Fig. 15, the stop count increases every 100us. If the stop count equals to 20000, the speed command is reduced to zero directly. The real speed ( v ) cannot follow the speed command ( v* ) because the user grasps the wheelchair wheels to reduce the speed.

Fig. 17.Experimental result of the quick stop of the speed.

 

V. CONCLUSION

In this paper, new operation and control strategies for the PAW of a manual wheelchair was proposed. The motion recognition was implemented in the PAW control system by the detection of the acceleration sensor output signal. The speed of the wheelchair was increased step by step according to external force applied by the user. In the brake operation, the user reduces the speed step by step or quickly and the controller determines whether the step by step or quick speed reduction is required according to the time duration of the acceleration. The validity of the proposed algorithm was verified through experimental results.

This research was financially supported by the INNOPOLIS Foundation (14BSI388)