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A simulation and experimental study of dynamic performance and electric consumption of an electric bicycle
Available online at www.sciencedirect.com
ScienceDirect ScienceDirect
Energyonline Procedia 00 (2018) 000–000 Available onlineatat www.sciencedirect.com Available www.sciencedirect.com Energy Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia 158 Energy Procedia 00(2019) (2017)2865–2871 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
A simulation and experimental study of dynamic performance and A simulation experimental study dynamic and The and 15th International Symposium on of District Heating performance and Cooling electric consumption of an electric bicycle electric consumption of an electric bicycle Assessing the feasibility of using the Lim heat 1 1, demand-outdoor Nguyen Ba Hung , Octaeck * 1 Nguyen Balong-term Hung , Octaeck Lim1,*heat demand forecast temperature function for a district School of Mechanical Engineering University of Ulsan, Mugeo-dong, Nam-gu, Ulsan 44610, South Korea 1
School of Mechanical Engineering University of Ulsan, Mugeo-dong, Nam-gu, Ulsan 44610, South Korea
1
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Abstract IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmesthe Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Nantes, A study is conducted to examine dynamic performance and electric consumption of an Kastler, electric 44300 bicycle basedFrance on the effects of A study operating is conducted to examine dynamic andthe electric consumption of an electric bicycle the based on the effects of various conditions. Tothe simulate theperformance operation of electric bicycle, this study establishes simulation models various Toelectric simulate the operation of models. the electric bicycle, this models study establishes simulation models includingoperating dynamic conditions. models of the bicycle and battery These simulation are solved the by Matlab-Simulink to including dynamic models of the electric bicycle andbicycle. batteryThe models. These simulationconditions models are solved bydensity Matlab-Simulink to provide the operating characteristics of the electric effects of operating such as air and slope on Abstract provide the operating characteristics of of thethe electric bicycle. of operating conditionsresults such as air density slope on the dynamics and electric consumption electric bicycleThe areeffects investigated. The simulation show that the and reduction of the dynamics electric consumption of the electric bicycle are investigated. simulation results show of air density andand slope results in an improvement of the dynamic performance andThe electric consumption. Asidethat fromthe thereduction simulation District networks addressed in thethe literature one ofelectric the consumption most effectivecharacteristics solutions for the decreasing the air density and slope results inisancommonly improvement of dynamic performance and consumption. Aside from simulation study, an heating experimental studyare also conducted to the examine dynamicasand electric of the electric greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat study, an experimental study is also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. This study shows agreements between simulation and experimental results at the same initial conditions. sales. Due theshows changed climate between conditions and building renovation results policies, heatsame demand the future could decrease, bicycle. This to study agreements simulation and experimental at the initialinconditions. prolonging the investment return period. Copyright © 2018 Elsevier Ltd. All rights reserved. main ofElsevier this paper isby toresponsibility assess the feasibility using the heat demand – outdoor temperature Conference function for on heatApplied demand ©The 2019 The Authors. Published Elsevier Ltd. Copyright ©scope 2018 Ltd. All rights reserved. Selection and peer-review under of the of scientific committee of the 10th International This is an and open access article underresponsibility thelocated CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) forecast. The district of Alvalade, in Lisbon (Portugal), was used as a case The district is consisted of 665 th study. Selection peer-review under of the scientific committee of the 10 International Conference on Applied Energy (ICAE2018). Peer-review under responsibility of the scientific of ICAE2018 – The 10th International Conference on Applied buildings that vary in both construction periodcommittee and typology. Three weather scenarios (low, medium, high) and threeEnergy. district Energy (ICAE2018). renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were Keywords: electric bicycle; dynamic model; battery model; Matlab-Simulink compared with results from a dynamic heat demand model, previously developed and validated by the authors. Keywords: electric bicycle; dynamic model; battery model; Matlab-Simulink The results showed that when only weather change is considered, the margin of error could be acceptable for some applications error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation 1.(the Introduction scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). 1. Introduction The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the The depletion of fossil fuels and global warming problem causedseason by exhaust emission from fossil-fueled vehicles decrease in the number of heating hours of 22-139h during the heating (depending on the combination of weather and The depletion of fossil fuels and global warming problem caused by exhaust emission from fossil-fueled vehicles are becoming motivations for researchers to develop the alternative fuels as well as new vehicles. One renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (dependingofonthe the are becoming motivations researchers tobedevelop alternative fuelsparameters asthewell as new vehicles. One of the potential solutions is thevalues useforof electriccould vehicles (EVs) which help to reduce toxic andconsidered, improve coupled scenarios). The suggested used to the modify the function foremissions the scenarios and potential solutions use of electric vehicles (EVs) which help to reduce the toxic emissions and improve the improve the accuracyisofthe heat demand estimations.
© 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +82-052-259-2852; fax: +82-052-259-1680. Cooling. E-mail address: [email protected] * Corresponding author. Tel.: +82-052-259-2852; fax: +82-052-259-1680. E-mail address: [email protected]
Keywords: Heat demand; Forecast; change 1876-6102 Copyright © 2018Climate Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.937
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2866 2
energy security problems [1],[2],[3],[4], and [5]. Among the EVs, electric bicycle is being received a great attention from people and researchers over the world due to its wide application potentials. In general, the electric bicycles are not only suitable for driving on many varied terrains such as flat, hilly, and mixed terrains, but also more practical in terms of accessibility, price, maintenance, and repairs than other EVs [6]. Many previous studies for the electric bicycles have been conducted [1],[2],[4],[7],[8],[9],[10], and [11]. Cardone et al. [7] presented dynamic models and controller designs based on a torque control of a power-assisted electric bicycle, in which the input is the voltage to the electric motor. A performance evaluation for an electric bicycle was conducted by Muetze et al. [8], in which the total power required of the electric bicycle was examined under the effects of rider mass, slope and wind speed. Abagnale et al. [9] presented a performance and environmental analysis of an electric bicycle which was compared to a thermal moped. It can be found that the previous studies showed useful information in studying and designing of the electric bicycles. However, the previous studies rarely mentioned the effects of operating conditions on the electric consumption which is considered as one of important factors when designing a high performance electric bicycle. This paper presents a simulation study of the dynamics and electric consumption of an electric bicycle under the effects of operating conditions such as air density and slope. The simulation models including dynamic and battery models are established to describe the operation of the electric bicycle. These models are calculated and solved by a code programmed in Matlab-Simulink. In addition, an experimental study is also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. 2. Simulation study 2.1. Bicycle dynamic models Fig. 1 shows a force analysis model of the electric bicycle, in which the rider’s power is assisted by an electric motor during pedaling.
Fig. 1 Force analysis model of the electric bicycle
The motion of bicycle obeys Newton’s second law, which is described by:
Fp Fw Fr Fs M
d 2x dt 2
(1)
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2867 3
Where Fp is propulsion force, Fr is rolling resistance force [1], Fs is slope resistance force (Fs=9.81.G.M, with G is slope grade), Fw is wind resistance force [1], M is total mass of bicycle (Mb) and rider (Mr), and x is distance (m). The electric bicycle uses a DC electric motor installed in the rear wheel. The electric motor receives the control signals detected by rider’s torque when pedaling to generate a motor torque which assists the rider’s power. The dynamics of the DC electric motor are modeled by equations shown below [12]:
dia ia (t ) Ra K bm U a dt
(2)
dm B1m TL K bia (t ) dt
(3)
La J
Where La is the armature inductance, Ra is the armature resistance, ia is the armature current, Kb is the back emf constant, Ua is the terminal voltage of DC motor, J is torque of inertia, ωm is the speed motor, B1 is the viscous friction coefficient, and TL is the load torque. 2.2. Battery model A lithium-ion battery is used to provide the input voltage to the electric motor. The battery model used in this study is described by a discharge model [13],[14] which presents the decrease of battery voltage as a function of current. Namely, the discharge model of the lithium-ion battery is shown as below:
Vb E0 K
Q Q i(t ) K i * Ri Ae( Bi(t )) Q i(t ) Q i(t )
(4)
where Vb is battery voltage, E0 is battery constant voltage, K is polarization constant, Q is battery capacity, i(t) is actual battery charge (i(t)=ʃ idt ), A is exponential zone amplitude, B is exponential zone time constant inverse, R is internal resistance, i is battery current, and i* is filtered current. 2.3. Simulation results Air density is one of factors affecting the operation of the electric bicycle because it relates to wind resistance force against the motion of the electric bicycle. The effects of the air density on the velocity and distance of the electric bicycle are described in Fig. 2. The results show that the bicycle velocity increases 2.7 % when the air density is reduced from 1.225 kg/m3 to 1.145 kg/m3. As a result, the distance is increased when the air density is reduced, as shown in Fig. 2(a). The effects of air density on the electric consumption are shown in Fig. 2(b). It can be found that the increase of air density results in an increased electric consumption of 0.08 % through the reduction of battery voltage.
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2868 4 30
37 Initial conditions: vw=0 m/s G=0 % Mr =57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m
Velocity [km/h]
20
Battery voltage [V]
25
Air density = 1.145 kg/m3 Air density = 1.183 kg/m3 Air density = 1.225 kg/m3
15
Initial conditions: vw=0 m/s G=0 % Mr=57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m
10
5
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Air density = 1.145 kg/m3 Air density = 1.183 kg/m3 Air density = 1.225 kg/m3
36
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150 200 250 Distance [m]
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0
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(a)
30 Time [s]
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(b)
Fig. 2 (a) Effects of air density on velocity and distance; (b) Effects of air density on electric consumption 30
37 Initial conditions: vw=0 m/s G=0 % Mr =57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m
25
G=0 % G = 0.87 % G = 1.74 %
Battery voltage [V]
Velocity [km/h]
20
15 Initial conditions: vw=0 m/s Mr=57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m Air density = 1.145 kg/m 3
10
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G=0% G = 0.87 % G = 1.74 %
36
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50
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150 200 250 Distance [m]
(a)
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0
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20
30 Time [s]
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(b)
Fig. 3 (a) Effects of slope on velocity and distance; (b) Effects of slope on electric consumption
Slope grade (G) directly affects the motion of the electric bicycle due to its relationship with slope resistance force shown in Eq.(1). Fig. 3 shows the effects of the slope on the velocity, distance and electric consumption of the electric bicycle. As shown in Fig. 3(a), the bicycle velocity significantly reduces about 8.1 % when the slope grade is increased from 0 % to 1.74 %. The reduction of velocity leads to a reduction of distance, as observed in Fig. 3 (a). It can be found that the increase of slope grade results in a greater electric consumption through a battery voltage reduction, as shown in Fig. 3(b). The electric consumption increases 0.25 % when the slope grade is increased from 0 % to 1.74 %
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2869 5
3. Experimental study 3.1. Experimental system setup Fig. 4 shows an experimental system for the electric bicycle. This experimental system includes an electric bicycle equipped with a lithium-ion battery, and a DC electric motor installed in the rear wheel. In addition, the electric bicycle is also equipped with the signal processing and measurement devices to collect the experimental data, as shown in Fig. 4.
Fig. 4 Experimental system
3.2. Experimental results The experimental results are presented in Fig. 5, which include the distance, velocity and electric consumption of the electric bicycle. Simulation Experiment
350
Simulation Experiment
30
300
Simulation Experiment 36.5
250 200 150
nitial conditions: vw=0 m/s G=0 % M r=57 kg M b=21 kg Rw=0.33 m Lc=0.170 m
100 50
Battery voltage [V]
25
Velocity [km/h]
Distance [m]
37
35
400
20 15 Initial conditions: vw=0 m/s G=0 % Mr=57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m
10 5
36
35
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0 0
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(a)
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Initial conditions: vw=0 m/s G=0 % Mr =57 kg Mb=21 kg Rw=0.33 m Lc=0.170 m
35.5
0
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(b)
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(c)
Fig. 5 (a) Distance; (b) Velocity; (c) Electric consumption
As shown in Fig. 5, the experimental results are compared with the simulation results in the same initial conditions, including wind speed vw=0 m/s, slope grade G=0 %, rider mass Mr=57 kg, bicycle mass Mb=21 kg, radius of wheel Rw=0.33 m, and crank length Lc=0.170 m. It can be seen that the experimental results have the same trend with the simulation results in moving distance, velocity and battery voltage. The fluctuation of experimental battery voltage could be due to the fluctuation of experimental velocity as shown in Fig. 5(b).
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Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
4. Conclusion An electric bicycle has been modeled and simulated based on the dynamics and battery models. These simulation models have been solved by a program written in Matlab-Simulink. The effects of input parameters such as air density and slope on the dynamic performance and electric consumption of the electric bicycle were investigated. The simulation results showed that the reduction of air density from 1.225 kg/m3 to 1.145 kg/m3 resulted in increasing the bicycle velocity, while the electric consumption was reduced 0.08 %. In addition, the simulation results showed that the electric bicycle should not be run on the slope terrains (G>0 %) which resulted in increasing the electric consumption as well as reducing the bicycle velocity. An experimental study was also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. This study showed that the experimental results agreed with the simulation results at the same initial conditions. In the next work, a detailed study with the effects of more input parameters will be conducted to develop a high efficiency electric bicycle. Acknowledgements This research was financially supported by the "Development and Promotion of Electric Bus in Thailand" through the Ministry of Trade Industry & Energy (MOTIE) and Korea Institute of Energy Technology Evaluation and Planning all rights reserved (KETEP). This work was supported by Upbringing Business with Innovative Urban Public Institutions by the Ministry of Trade, Industry and Energy (MOTIE, Korea)[Project Name: Establishment of Battery/ESS-Based Energy Industry Innovation Ecosystem]. References [1] Hung N.B, Sung J, Lim O. A study of the effects of input parameters on the dynamics and required power of an electric bicycle. Applied Energy 2017;204:1347-1362. [2] Hung N.B, Sung J, Lim O. A simulation and experimental study of operating performance of an electric bicycle integrated with a semiautomatic transmission. Applied Energy 2018;221:319-333. [3] Alves J, Baptista P.C, Goncalves G.A, Duarte G.O. Indirect methodologies to estimate energy use in vehicles: Application to battery electric vehicles. Energy Conversion and Management 2016;124:116-129. [4] Hung N.B, Sung J, Kim K, Lim O. A Simulation and Experimental Study of Operating Characteristics of an Electric Bicycle. Energy Procedia 2017;105:2512-2517. [5] Ferrero E, Alessandrini S, Balanzino A. Impact of the electric vehicles on the air pollution from a highway. Applied Energy 2016;169:450459. [6] Wang Q, Jiang B, Li B, Yan Y. A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles. Renewable and Sustainable Energy Reviews 2016;64:106-128. [7] Cardone M, Strano S, Terzo M. Optimal power-assistance system for a new pedelec model. Proc. ImechE Part C: J. Mechanical Engineering Science 2015;230:3012-3025. [8] Muetze A, Tan Y.C. Electric bicycles: A performance evaluation. IEEE Industry Applications Magazine 2011;13:12-21. [9] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. A dynamic model for the performance and environmental analysis of an innovative e-bike. Energy Procedia 2015;81:618-627. [10] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Model-based control for an innovative power-assisted bicycle. Energy Procedia 2015;81:606-617. [11] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Derivation and Validation of a Mathematical Model for a Novel Electric Bicycle. Proceedings of the World Congress on Engineering, London, U.K, 2015. [12] Yildiz A.B. Electrical equivalent circuit based modeling and analysis of direct current motors. Electrical Power and Energy Systems 2012;43:1043-1047. [13] Tremblay O, Dessaint L.A. Experimental Validation of a Battery Dynamic Model for EVApplications. World Electric Vehicle Journal 2009;3:0289-0298.
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
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[14] Patil P.J, Koujalagi J.P. Modeling of BLDC motor Powered from Li-ion Battery for Electric Bicycle Application. International Journal for Research in Science & Advanced Technologies 2014;2:047-053.
ScienceDirect ScienceDirect
Energyonline Procedia 00 (2018) 000–000 Available onlineatat www.sciencedirect.com Available www.sciencedirect.com Energy Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia 158 Energy Procedia 00(2019) (2017)2865–2871 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
A simulation and experimental study of dynamic performance and A simulation experimental study dynamic and The and 15th International Symposium on of District Heating performance and Cooling electric consumption of an electric bicycle electric consumption of an electric bicycle Assessing the feasibility of using the Lim heat 1 1, demand-outdoor Nguyen Ba Hung , Octaeck * 1 Nguyen Balong-term Hung , Octaeck Lim1,*heat demand forecast temperature function for a district School of Mechanical Engineering University of Ulsan, Mugeo-dong, Nam-gu, Ulsan 44610, South Korea 1
School of Mechanical Engineering University of Ulsan, Mugeo-dong, Nam-gu, Ulsan 44610, South Korea
1
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Abstract IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmesthe Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Nantes, A study is conducted to examine dynamic performance and electric consumption of an Kastler, electric 44300 bicycle basedFrance on the effects of A study operating is conducted to examine dynamic andthe electric consumption of an electric bicycle the based on the effects of various conditions. Tothe simulate theperformance operation of electric bicycle, this study establishes simulation models various Toelectric simulate the operation of models. the electric bicycle, this models study establishes simulation models includingoperating dynamic conditions. models of the bicycle and battery These simulation are solved the by Matlab-Simulink to including dynamic models of the electric bicycle andbicycle. batteryThe models. These simulationconditions models are solved bydensity Matlab-Simulink to provide the operating characteristics of the electric effects of operating such as air and slope on Abstract provide the operating characteristics of of thethe electric bicycle. of operating conditionsresults such as air density slope on the dynamics and electric consumption electric bicycleThe areeffects investigated. The simulation show that the and reduction of the dynamics electric consumption of the electric bicycle are investigated. simulation results show of air density andand slope results in an improvement of the dynamic performance andThe electric consumption. Asidethat fromthe thereduction simulation District networks addressed in thethe literature one ofelectric the consumption most effectivecharacteristics solutions for the decreasing the air density and slope results inisancommonly improvement of dynamic performance and consumption. Aside from simulation study, an heating experimental studyare also conducted to the examine dynamicasand electric of the electric greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat study, an experimental study is also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. This study shows agreements between simulation and experimental results at the same initial conditions. sales. Due theshows changed climate between conditions and building renovation results policies, heatsame demand the future could decrease, bicycle. This to study agreements simulation and experimental at the initialinconditions. prolonging the investment return period. Copyright © 2018 Elsevier Ltd. All rights reserved. main ofElsevier this paper isby toresponsibility assess the feasibility using the heat demand – outdoor temperature Conference function for on heatApplied demand ©The 2019 The Authors. Published Elsevier Ltd. Copyright ©scope 2018 Ltd. All rights reserved. Selection and peer-review under of the of scientific committee of the 10th International This is an and open access article underresponsibility thelocated CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) forecast. The district of Alvalade, in Lisbon (Portugal), was used as a case The district is consisted of 665 th study. Selection peer-review under of the scientific committee of the 10 International Conference on Applied Energy (ICAE2018). Peer-review under responsibility of the scientific of ICAE2018 – The 10th International Conference on Applied buildings that vary in both construction periodcommittee and typology. Three weather scenarios (low, medium, high) and threeEnergy. district Energy (ICAE2018). renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were Keywords: electric bicycle; dynamic model; battery model; Matlab-Simulink compared with results from a dynamic heat demand model, previously developed and validated by the authors. Keywords: electric bicycle; dynamic model; battery model; Matlab-Simulink The results showed that when only weather change is considered, the margin of error could be acceptable for some applications error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation 1.(the Introduction scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). 1. Introduction The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the The depletion of fossil fuels and global warming problem causedseason by exhaust emission from fossil-fueled vehicles decrease in the number of heating hours of 22-139h during the heating (depending on the combination of weather and The depletion of fossil fuels and global warming problem caused by exhaust emission from fossil-fueled vehicles are becoming motivations for researchers to develop the alternative fuels as well as new vehicles. One renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (dependingofonthe the are becoming motivations researchers tobedevelop alternative fuelsparameters asthewell as new vehicles. One of the potential solutions is thevalues useforof electriccould vehicles (EVs) which help to reduce toxic andconsidered, improve coupled scenarios). The suggested used to the modify the function foremissions the scenarios and potential solutions use of electric vehicles (EVs) which help to reduce the toxic emissions and improve the improve the accuracyisofthe heat demand estimations.
© 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +82-052-259-2852; fax: +82-052-259-1680. Cooling. E-mail address: [email protected] * Corresponding author. Tel.: +82-052-259-2852; fax: +82-052-259-1680. E-mail address: [email protected]
Keywords: Heat demand; Forecast; change 1876-6102 Copyright © 2018Climate Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.937
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2866 2
energy security problems [1],[2],[3],[4], and [5]. Among the EVs, electric bicycle is being received a great attention from people and researchers over the world due to its wide application potentials. In general, the electric bicycles are not only suitable for driving on many varied terrains such as flat, hilly, and mixed terrains, but also more practical in terms of accessibility, price, maintenance, and repairs than other EVs [6]. Many previous studies for the electric bicycles have been conducted [1],[2],[4],[7],[8],[9],[10], and [11]. Cardone et al. [7] presented dynamic models and controller designs based on a torque control of a power-assisted electric bicycle, in which the input is the voltage to the electric motor. A performance evaluation for an electric bicycle was conducted by Muetze et al. [8], in which the total power required of the electric bicycle was examined under the effects of rider mass, slope and wind speed. Abagnale et al. [9] presented a performance and environmental analysis of an electric bicycle which was compared to a thermal moped. It can be found that the previous studies showed useful information in studying and designing of the electric bicycles. However, the previous studies rarely mentioned the effects of operating conditions on the electric consumption which is considered as one of important factors when designing a high performance electric bicycle. This paper presents a simulation study of the dynamics and electric consumption of an electric bicycle under the effects of operating conditions such as air density and slope. The simulation models including dynamic and battery models are established to describe the operation of the electric bicycle. These models are calculated and solved by a code programmed in Matlab-Simulink. In addition, an experimental study is also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. 2. Simulation study 2.1. Bicycle dynamic models Fig. 1 shows a force analysis model of the electric bicycle, in which the rider’s power is assisted by an electric motor during pedaling.
Fig. 1 Force analysis model of the electric bicycle
The motion of bicycle obeys Newton’s second law, which is described by:
Fp Fw Fr Fs M
d 2x dt 2
(1)
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
2867 3
Where Fp is propulsion force, Fr is rolling resistance force [1], Fs is slope resistance force (Fs=9.81.G.M, with G is slope grade), Fw is wind resistance force [1], M is total mass of bicycle (Mb) and rider (Mr), and x is distance (m). The electric bicycle uses a DC electric motor installed in the rear wheel. The electric motor receives the control signals detected by rider’s torque when pedaling to generate a motor torque which assists the rider’s power. The dynamics of the DC electric motor are modeled by equations shown below [12]:
dia ia (t ) Ra K bm U a dt
(2)
dm B1m TL K bia (t ) dt
(3)
La J
Where La is the armature inductance, Ra is the armature resistance, ia is the armature current, Kb is the back emf constant, Ua is the terminal voltage of DC motor, J is torque of inertia, ωm is the speed motor, B1 is the viscous friction coefficient, and TL is the load torque. 2.2. Battery model A lithium-ion battery is used to provide the input voltage to the electric motor. The battery model used in this study is described by a discharge model [13],[14] which presents the decrease of battery voltage as a function of current. Namely, the discharge model of the lithium-ion battery is shown as below:
Vb E0 K
Q Q i(t ) K i * Ri Ae( Bi(t )) Q i(t ) Q i(t )
(4)
where Vb is battery voltage, E0 is battery constant voltage, K is polarization constant, Q is battery capacity, i(t) is actual battery charge (i(t)=ʃ idt ), A is exponential zone amplitude, B is exponential zone time constant inverse, R is internal resistance, i is battery current, and i* is filtered current. 2.3. Simulation results Air density is one of factors affecting the operation of the electric bicycle because it relates to wind resistance force against the motion of the electric bicycle. The effects of the air density on the velocity and distance of the electric bicycle are described in Fig. 2. The results show that the bicycle velocity increases 2.7 % when the air density is reduced from 1.225 kg/m3 to 1.145 kg/m3. As a result, the distance is increased when the air density is reduced, as shown in Fig. 2(a). The effects of air density on the electric consumption are shown in Fig. 2(b). It can be found that the increase of air density results in an increased electric consumption of 0.08 % through the reduction of battery voltage.
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
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Fig. 3 (a) Effects of slope on velocity and distance; (b) Effects of slope on electric consumption
Slope grade (G) directly affects the motion of the electric bicycle due to its relationship with slope resistance force shown in Eq.(1). Fig. 3 shows the effects of the slope on the velocity, distance and electric consumption of the electric bicycle. As shown in Fig. 3(a), the bicycle velocity significantly reduces about 8.1 % when the slope grade is increased from 0 % to 1.74 %. The reduction of velocity leads to a reduction of distance, as observed in Fig. 3 (a). It can be found that the increase of slope grade results in a greater electric consumption through a battery voltage reduction, as shown in Fig. 3(b). The electric consumption increases 0.25 % when the slope grade is increased from 0 % to 1.74 %
Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
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3. Experimental study 3.1. Experimental system setup Fig. 4 shows an experimental system for the electric bicycle. This experimental system includes an electric bicycle equipped with a lithium-ion battery, and a DC electric motor installed in the rear wheel. In addition, the electric bicycle is also equipped with the signal processing and measurement devices to collect the experimental data, as shown in Fig. 4.
Fig. 4 Experimental system
3.2. Experimental results The experimental results are presented in Fig. 5, which include the distance, velocity and electric consumption of the electric bicycle. Simulation Experiment
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Fig. 5 (a) Distance; (b) Velocity; (c) Electric consumption
As shown in Fig. 5, the experimental results are compared with the simulation results in the same initial conditions, including wind speed vw=0 m/s, slope grade G=0 %, rider mass Mr=57 kg, bicycle mass Mb=21 kg, radius of wheel Rw=0.33 m, and crank length Lc=0.170 m. It can be seen that the experimental results have the same trend with the simulation results in moving distance, velocity and battery voltage. The fluctuation of experimental battery voltage could be due to the fluctuation of experimental velocity as shown in Fig. 5(b).
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Nguyen Ba Hung et al. / Energy Procedia 158 (2019) 2865–2871 Author name / Energy Procedia 00 (2018) 000–000
4. Conclusion An electric bicycle has been modeled and simulated based on the dynamics and battery models. These simulation models have been solved by a program written in Matlab-Simulink. The effects of input parameters such as air density and slope on the dynamic performance and electric consumption of the electric bicycle were investigated. The simulation results showed that the reduction of air density from 1.225 kg/m3 to 1.145 kg/m3 resulted in increasing the bicycle velocity, while the electric consumption was reduced 0.08 %. In addition, the simulation results showed that the electric bicycle should not be run on the slope terrains (G>0 %) which resulted in increasing the electric consumption as well as reducing the bicycle velocity. An experimental study was also conducted to examine the dynamic and electric consumption characteristics of the electric bicycle. This study showed that the experimental results agreed with the simulation results at the same initial conditions. In the next work, a detailed study with the effects of more input parameters will be conducted to develop a high efficiency electric bicycle. Acknowledgements This research was financially supported by the "Development and Promotion of Electric Bus in Thailand" through the Ministry of Trade Industry & Energy (MOTIE) and Korea Institute of Energy Technology Evaluation and Planning all rights reserved (KETEP). This work was supported by Upbringing Business with Innovative Urban Public Institutions by the Ministry of Trade, Industry and Energy (MOTIE, Korea)[Project Name: Establishment of Battery/ESS-Based Energy Industry Innovation Ecosystem]. References [1] Hung N.B, Sung J, Lim O. A study of the effects of input parameters on the dynamics and required power of an electric bicycle. Applied Energy 2017;204:1347-1362. [2] Hung N.B, Sung J, Lim O. A simulation and experimental study of operating performance of an electric bicycle integrated with a semiautomatic transmission. Applied Energy 2018;221:319-333. [3] Alves J, Baptista P.C, Goncalves G.A, Duarte G.O. Indirect methodologies to estimate energy use in vehicles: Application to battery electric vehicles. Energy Conversion and Management 2016;124:116-129. [4] Hung N.B, Sung J, Kim K, Lim O. A Simulation and Experimental Study of Operating Characteristics of an Electric Bicycle. Energy Procedia 2017;105:2512-2517. [5] Ferrero E, Alessandrini S, Balanzino A. Impact of the electric vehicles on the air pollution from a highway. Applied Energy 2016;169:450459. [6] Wang Q, Jiang B, Li B, Yan Y. A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles. Renewable and Sustainable Energy Reviews 2016;64:106-128. [7] Cardone M, Strano S, Terzo M. Optimal power-assistance system for a new pedelec model. Proc. ImechE Part C: J. Mechanical Engineering Science 2015;230:3012-3025. [8] Muetze A, Tan Y.C. Electric bicycles: A performance evaluation. IEEE Industry Applications Magazine 2011;13:12-21. [9] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. A dynamic model for the performance and environmental analysis of an innovative e-bike. Energy Procedia 2015;81:618-627. [10] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Model-based control for an innovative power-assisted bicycle. Energy Procedia 2015;81:606-617. [11] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Derivation and Validation of a Mathematical Model for a Novel Electric Bicycle. Proceedings of the World Congress on Engineering, London, U.K, 2015. [12] Yildiz A.B. Electrical equivalent circuit based modeling and analysis of direct current motors. Electrical Power and Energy Systems 2012;43:1043-1047. [13] Tremblay O, Dessaint L.A. Experimental Validation of a Battery Dynamic Model for EVApplications. World Electric Vehicle Journal 2009;3:0289-0298.
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