Determining Fatigue Threshold according to Burned Calories for Energy Management in Pedal-Assist Electric Bike Riding

The There are different to calories and Determining Fatigue Threshold according to Burned Calories for Energy Management in Pedal-Assist Electric Bike Riding. Biomed

The Pedal assist electric bike consists of two electric and human propulsions. One of the interesting ideas that can be developed on electric bicycles is equipping the bike with a switch controller in order to change the power source between human and electric power sources. In the process of doing this research, it is necessary to recognize the driving force of humans, so it is possible to make a balance between two energy sources. In the first part of this paper, a model for calorie burning is designed during cycling, according to the relationship between heart rate and physical characteristics such as weight, age, and gender, then the effect of weight and age on the amount of burned calories is investigated. For the validity of the relation between heart rate and calorie burning, it is compared with online software. After designing the model, by performing metabolic tests, the maximum amount of calorie that a driver will not get tired for the age range from 25 to 35 years and weight 90Kg has been obtained, which is 180Kcal. For ages from 15 to 25 and from 35 to 45 years and weight 90kg, these values are equal to 186Kcal and 175Kcal, respectively. Also, with using online software and curve fitting for other age and weight ranges, the relationships have been created to estimate maximum burned calorie for wider physical body situation range in the condition that driver will not get tired. accurate enough. This method obtains the consumed energy and metabolic information of the driver in different environmental conditions. This method is alike DLW because specialties' attendance is required also. Due to this reason, it becomes expensive. The acceleration measurement is a rough method but it is inexpensive.
Monitoring the heart rate is a simple measurement method for calculating human energy consumption [11]. According to the studies, it is necessary to have mathematical relationships that can predict the performance of human driving forces. Monitoring the heart rate is not an accurate method for a low level of mobility and exercise.
In this paper, due to the energy consumption that is calculated in high active performance, this method is practical. Mi Band 3 is used as a heart rate sensor. By performing experimental tests and using online software, the relationships will be created to relate the heart rate and burned calorie.

Metabolic Activity
The corresponding e-bike is equipped with two types of power sources such as electric and human power. The electric power source system consists of battery, electric motor, and, controller. In this Section, the purpose is to investigate factors on human power generation. The human power generation has tight relation with metabolic parameters such as the driver's heart rate, maximum oxygen consumed volume, weight, gender, and, age. One important issue should be discussed is to determine the fatigue threshold. People have different fatigue threshold, so, there are some proposed means to measure the estimation of this value for any person. In this paper, the driver's fatigue level is determined by burned calories in a certain sport activity. Equation (1) expresses a relation between driver's physics such as heart rate hr in beat per minute (bpm), gender, age a considering year, weight w in kilogram unit, and burned calories Cal in kilocalorie unit [14].
There is a linear relation between passed time t and burned calorie rate. As was discussed in Introduction Section, an online software named "Keisan online calculator" is used to calculate the burned calories. This software works based on Equation (2) to obtain burned calories.

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Equation (2) expresses the burned calories Ex in kilocalories per minute. MET is muscle energy technique that is evaluated according to Table 1 is given further [13,14].  Table 2. The results are obtained and shown also. Table 2 shows the validity of Equations (1) and (2). Because they are approximately equal. Figure 1 shows this equality. It is comprehended in Figure 1 that there is a linear relationship between weight and burning calories. To investigate more factors, it is important to consider age variations. Table 3 shows the burned calories are obtained with Keisan online calculator software. Table 3 shows the wide range of ages to cover all someone's lifetime. Like Figure 1, the age influence diagram is given in Figure 2. This diagram proves the validity of these two equations (1), (2). It is inferred that old people have slow calorie burning in comparison with youths. These people aged from 25 to 35 years old and weighed from 85 to 95Kg. Table 4 shows these four people's characteristics and results.
The purpose of these tests is to determine the tiredness threshold in young students. The students rode the bicycle to reach this threshold then they stop. According to Figure 3, At the beginning of the test, the heart rate gradually increases at the warm-up level.
After a while, the heart rate reaches its peak value. In this situation, the driver is close to the fatigue level. By feeling tired, the driver reduces the speed to stop the riding afterward. In recovery duration, the heart rate reduces due to driver low activity. As it is evident in Figure 3, the students have different recovery start time. Figure 4 shows the corresponding calorie burning to the driver's heart rate.
The burning calorie in these tests is obtained by Mi Band 3 heart rate sensor installed on the driver's wrist. The diagrams in Figure   4 are monotonically increasing functions. Because the calorie burning is accumulative. Table 5 shows the other eight peoples test and their results.    Table 3 according to the driver's mass range. The tiredness level is determined in burned calories (Kcal) to limit the maximum allowable calorie burning before the driver becomes tired. These factors are obtained by poly fitting among the data are extracted from online software. Equation (3) and Table 6 cover age and weight variables to find the tiredness level.

Conclusion
It is required to understand the performance of both human and electric power source for energy management in a pedal-assist electric bike. For recognizing the human power source, a test on students have been performed to determine the fatigue threshold for different physical body situation. Equation (3) is the fatigue threshold determiner. By poly fitting among the data that are obtained by experimental tests and online software, this equation is extended for other range of age and weight. This equation evaluates the maximum burned calorie in the condition that the cyclist will not get tired and this evaluation depends on the driver's age and weight. This is very useful to design a controller to switch between these two power sources. In other words, this is a basic step for making smart this knid of bicycles. After importing the route, the processor can make a plan for switching in a case that the driver could pass the route without getting tired and the battery level stays in a high position as much as possible.