Optimal power management strategy by using fuzzy logic controller for BLDC Motor-Driven E-Rickshaw

Abstract

In this paper, the authors have addressed the modeling and design of the BLDC Motor-Driven E-Rickshaw based on hybrid energy storage system (HESS) for optimum power management using fuzzy logic. In Hybrid energy sources, solar power is used to charge a battery (primary source) that is effectively coupled to supercapacitor (ancillary source) for peak demand supplies. A power-split control strategy is proposed to control the power supply by using the HESS Fuzzy Logic in different engine operating modes. Projected power layering improves the battery life cycle with the proper use of the Supercapacitor. By providing a new switching algorithm, the DC link voltage is boosted to effectively transfer power to the HESS unit. Fuzzy logic-based HESS provides better performance in electric vehicles, such as deep discharge protection of the battery, and faster acceleration. Also, there is a quick comparison of E-rickshaw solar power with traditional E-rickshaw. The planned design model was simulated by MATLAB^®/Simulink environment.

Keywords

Solar power battery optimal power management (OPM)BLDC E-Rickshaw fuzzy logic controller (FLC)Supercapacitor

1 Introduction

The attention paid to ELECTRIC VEHICLES (EV) is increasing because they can provide many special, positive features such as low greenhouse emissions, high efficiency, silent operation, fine control over conventional vehicles, etc [1]. Electric Vehicles have the potential for green transporting technology that could lead to the automotive sector shortly [2]. India has the leading 3-wheeler auto-rickshaw industry for short-distance transportation [3]. The auto-rickshaw was chosen as the best preferred low-speed, small-distance vehicle for transportation every day. There has been a great deal of ingenuity to launch the battery-activated E-rickshaws in India [4].

The energy storage system is a fundamental part of EV’s. Lead-acid batteries are commonly used as primary energy storage in E-rickshaw. There are, however, certain deficiencies, such as high costs due to the availability and disposal of materials used, a limited life cycle, a limited power density, etc. [5]. Double-layer condensers, known as supercapacitors, are used to correct these disadvantages, offering some exceptional features for example high-power density, long life cycle, and wide operating temperature range [6]. Although the supercapacitor delivers better efficiency in many ways, it cannot be used as the main ESS because it has a relatively small energy density [7]. Also, because the supercapacitors have recently been developed, it is not as reliable as conventional batteries [8].

Li-ion ‘s battery is a successful vehicle application technology. However, the life of the Li-ion battery can be significantly reduced if the battery is exposed to rapid loading and unloading current to respond to rapid changes in traction engine torque power. The Supercapacitor can help the battery pack meet high power requirements while driving hills and high torque requirements. It also improves vehicle acceleration and smooth non-pulsating driving, due to its high specific energy and relatively higher power relative to lead-acid batteries and NiMH batteries [1 –3].

The proposed system uses a unidirectional DC-DC buck converter to control the flow of power in between the supercapacitor and the battery, along with a novel Fuzzy Logic (FL) based controller for the BLDC motor. The engine is mainly driven by the battery. Sunlight solar energy is transformed into electricity using a PV panel that is used to charge a separate battery during the day when the sun shines [9]. The FOC control technique is used to control the speed and torque of the vehicle for the proposed system. The dc-link voltage is boosted during braking using an appropriate inverter switching algorithm [24]. The braking energy is collected directly from the supercapacitor module and the battery pack without the power converter being used. The FOC control method increases the dc-link voltage by varying the PWM in the inverter. Therefore, when the supercapacitor is charged to the maximum voltage, the battery pack enables regenerative braking and improves efficiency. Besides, the Fuzzy logic is used to distribute the braking force for reliable vehicle braking [10].

The supply of power is depending on the selection of loads such as dynamic, static load, and transient load [25]. The main contribution of this paper is

Battery life Improvement

Optimal Power Utilization of ESS

Power Split management by FLC

The rest paper is arranged as following: Section 2 provides the structure & design of the E-rickshaw. Section 3. Discuss the mathematical modeling of Battery & supercapacitor. Section 4 discusses the Fuzzy Logic Controller and Implementation in E-rickshaw. Section 5 shows the simulation results and discussion. Section 6 discusses the Conclusion of this research paper.

2 System description & modelling of each component

The schematic structural diagram of E-rickshaw is considered as a purely electric driven vehicle system [11]. In this system battery & Supercapacitor chosen as a dual Energy Storage System presented in Fig. 1. This arrangement works as a partially active parallel configuration for interconnecting SC and battery. In this system, the battery is considered as the primary source, even though the supercapacitor works as an auxiliary source and the solar panel is used to charge the battery in operating condition. In this structure, the battery is associated with the DC-link directly to sustain the constant voltage of the DC link, and the auxiliary energy storage device is associated over a DC to DC buck-boost converter. The methodology to the modeling of various system components is essential to the realization of EVs as designing and evaluating system performance [12, 13].

Fig. 1

Generalized schematic vehicle drive structure.

2.1 Calculation of maximum solar radiation

Projected radiation on a given Photovoltaic array at a particular location is calculated by the subsequent equation expressed in [15]: $S_{module} = S_{incident} sin ([90 - φ + δ] + β)$ (1) Where:

S _module:	Incident Solar radiation on PV array in w/m²
S_incident:	Perpendicularly measured solar radiation with solar in w/m²
φ:	Latitude of the selected areas in the degree
δ:	The declined angle measured in degree
β:	The tilt angle of PV module with horizontal in degree

$δ = 23 . 45 \times Sin [360 / 365] \times (D + 284)$ (2) Where, D represents the day in a year.

2.2 Dynamic modeling of E-Rickshaw

According to the Motion’s law, a vehicle is designed according to the load by considering the force acting on it shown in Fig. 2.

Fig. 2

Acting force on a vehicle.

The traction force, F_T is essential to derive the wheels overwhelming opposite forces given below, [14] $F_{T} = F_{RR} + F_{WA} + F_{HC} + F_{AD} + F_{LA}$ (3) Where;

F_RR=Rolling Resistive Force

F_WA=Rolling Accelerating Force

F_HC=Hill Climbing Force

F_AD=Aerodynamic Drag

F_LA=Linear Accelerating Force

Expanded equation are shown below – $\begin{matrix} F_{T} = & C_{RR} Mg cos φ + \frac{1}{2} ρ {AC}_{D} V^{2} + Mg sin φ \\ + M \frac{dv}{dt} + 0.1 F_{LA} \end{matrix}$ (4) Where,

C_RR=Rolling resistance Coefficient

M = Vehicle Mass (Kg)

G = 9.81 m/s² (Gravitational Constant)

φ=Grade Angle in degree

ρ=Air density

If the velocity of vehicle is v, Then the Tractive Power, $P_{t} = F_{t} \times v$ (5) The Motor power requirement, calculated by the using of tractive power [14] $Motor Power, P_{m} = \frac{P_{t}}{η_{t}}; P_{t} ⩾ 0$ (6) $Motor Power, P_{m} = P_{t} {\times η}_{t}; P_{t} ∠ 0$ (7) Where,

η_trepresents the Transmission Efficiency.

Motor and Wheal Speed are related to the gear ratio (GR), expressed as $GR = \frac{N_{m} \times r_{w} \times π}{30 \times v_{max}}$ (8)

Where;

Nm = Maximum Rotor Speed (rev/min)

r_w = Radius of Wheel

v_max= Maximum Velocity of the Vehicle.

Wheel Torque can be calculated by given equation- $T_{req} = F_{T} \times r_{w}$ (9)

Capacity of Battery combination is chosen based on required power during a day as well as the efficiency [16].

The Capacity of the battery bank are explained by using the following expression [15]: $P_{b} = \frac{P_{r} t}{η_{b} V_{b} (DOD) n}$ (10)

Where;

P_r= Power Required

t = Operating Time

η_b= Battery Efficiency

V_b = Battery Voltage

DOD = Depth of discharge

n = days of autonomy

3 Mathematical modeling of hybrid energy storage system

E-rickshaw architecture has battery systems, dc-dc and dc-ac converters. To understand the system-level behavior, it is important to study the system level in presence of other. A modeling level approach is necessary to avoid the complexity of system interconnection and complexity. In this paper electrochemical modeling approach is applied for lithium-ion battery modeling. The modeling of the battery is shown in Fig. 3, SOC of the battery may be expressed effectively via battery performance [18 –21].

Fig. 3

Equivalent Model of Li-ion Battery.

3.1 Li-ion battery

The mathematical modeling approach is given by following equations that have been derived with the help of Fig. 3 [13], [22]

$U_{t} (k) = U_{oc} (k) - Up 1 (k) - Up 2 (k) - R_{0} t (k) * I_{t} (k - 1)$ (11) $U p 1 (k) = U p 1 (k - 1) - \frac{U p 1 (k - 1) k s}{R p 1 (k) C p 1 (k)} + \frac{I t (k - 1)}{C p 1 (k)}$ (12) $Up 2 (k) = Up 2 (k - 1) - \frac{Up 2 (k - 1) Ks}{R_{p 2} (k) C_{p 2} (k)} + \frac{I_{t} (k - 1) k_{s}}{C_{p 2} (k)}$ (13) $I_{t} (k) = - {QI}_{t} [{SOC (k) - SOC (k - 1)} / δ k]$ (14)

3.2 Supercapacitor

The modeling of supercapacitor is done with reference of Fig. 4. The detailed model is described in Equations 15 and 16 [13]. $V_{SC_t} {(t) = V}_{SC_1} {(k) - R}_{sc_es} I_{sc} (k - 1)$ (15) $V_{sc_1} {(k) = V}_{sc_1} (k - 1) - \frac{I_{sc} (k - 1)}{C_{0} {+ K}_{1} V_{sc_1} (k - 1)}$ (16)

Fig. 4

Equivalent model of Super-capacitor.

Where;

Vsc _t:	Terminal voltage
Rsc_es:	Series Resistance
Isc:	Discharging current of a cell respectively;
Vsc_1:	Voltage-dependent component’s voltage
C1:	Cell capacitance
Co:	Fixed component of cell capacitance
K1:	Constant parameter

4 Fuzzy logic controller

The fuzzy logic (FL) method is working as a brain. It is implemented in any system to decide the human brain regularly. The fuzzy logic controller is used in Electric vehicles because of its easiness, flexibility, and noble performance [6].

The Fuzzy Logic Controller is categorized into four subparts, given in Fig. 5. As follows

Fuzzification: Fuzzification is the process in which philological sets are found through the real assessment of the membership function.

Rule Base: This is intended with proficient expertise and governs the system operating requirement.

Interface with Engine: The fuzzy philological input is converted into a fuzzy philological output to the governing law specified in the fuzzy rule structure

Defuzzification: the philological fuzzy set is converted into the real assessment with the membership function.

Fig. 5

Overview of the FLC in a controlled system [1].

The membership function input variables graph is shown in Figs. 6 to 9. And the description in Table 1. The CS is found through the o/p signal of the FLC, which accumulates the system concert, match through pre-define inputs x (t), i.e. decided the i/p of the system y (t) to ensure the concert objectives.

Fig. 6

Slope membership function graph.

Fig. 7

Deep of discharge membership function graph.

Fig. 8

Speed membership function graph.

Fig. 9

Corrected speed membership function.

Table 1

Description of the fuzzy pattern

Linguistic variable of Fuzzy system	Grammar	Membership function used to represent the variables
SLOPE	Descending	Trapezoidal
	Flat	Triangle
	Ascending	Trapezoidal
DEEP OF DISCHARGE	Full	Trapezoidal
	High	Triangle
	Eco Mode	Trapezoidal
SPEED	Slow	Trapezoidal
	Normal	Triangle
	High	Trapezoidal
CORRECTED SPEED	Slow	Trapezoidal
	Normal	Triangle
	High	Trapezoidal

FLC is realistic to power management in EVs, it includes mainly three i/p: Vsc (Supercapacitor Voltage), P_demand, and battery C _ Rate, and single output which is then split power ratio (α) in b/w the P_{bat_demand} (battery power demand) and P_demand (Power Demand). This power-split ratio is defined as: $α = \frac{P_{Bat_Demand}}{P_{Demand}}$ (17) $P_{Demand} = P_{Bat_Demand} + P_{SC_Demand}$ (18)

A schematic diagram of the fuzzy logic (FL) controller by i/p and o/p are given in Fig. 5. By MATLAB toolbox, FL interpretation systems may be generated and modified via the graphical instruments and command-line function. Primarily, the entire energy management system by a block diagram is shown in Fig. 7 [6]. All input and output value points are varying in between 0 and 1. The input-output membership function is triangularly presented in Fig. 6. The proposed FLC has included rules for modes of operation and charging /discharging as well as the C-Rate [7, 8].

When the P_demand and V_SC_, voltage are high, controller angle α is lesser, consequently, the battery and supercapacitor tend to supply less power and high power. When the P_demand or V_SC voltage is low, the battery goes to discharge [23].

5 Results and discussions

The Energy Storage System (ESS) is used to store the excess electricity generated during the time of high irradiances or to sustain a steady supply of power to satisfy the load requirement during low irradiances. Conventional energy storage devices consisted of battery banks capable of processing and providing constant loading electricity. However, the high energy density that characterizes the batteries makes them the ultimate choice for a secure power supply, and the supply of a large surge of current through the battery reduces the battery’s life. The alternate approach is to pair batteries with a high-power density device capable of supplying a temporary surge current, such as a super capacitor. For such a hybrid device, the battery supplies constant energy while the super capacitor supplies immediate electricity to the load. The device suggested for this application is a stand-alone photovoltaic battery-SC HESS [25, 26]. The energy conservation strategy is introduced to monitor the production and distribution of resources in the network.

The irradiance 1000 W/m² up to 1 sec then it is changed to 400 W/m² at a constant temperature of 25 degrees. Figure 11 shows the current of Photo Voltaic, in which it provides the regular current up to 1 sec but changes at 1 sec. It shows the output current of PV is varies with irradiation of light. Figure 10 shows the Photovoltaic power, which also varies with irradiation of light. Figure 12 shows the output Voltage of PV.

Fig. 10

PV Power.

Fig. 11

PV current.

Fig. 12

PV Voltage.

Figure 13 shows the characteristics of Battery results. In which voltage is increasing from 0 to 1 because of negative, represents the charging of the battery by which the SOC of the battery increases in this duration but in the next step when the irradiation of the PV system is decreased then the system working as a supply to the load in which the battery discharge and the SOC are decreases and the current flows from battery to the load to fulfill the requirement of load, means it represents as a positive sign.

Fig. 13

Battery results.

Figure 14 shows the characteristics of Ultra-capacitor out results. In which at the time of high requirement of power, it supplies the power to the load shown in Fig. 15. and also shows the comparative power analysis of ultra-capacitor in addition to the battery of the Hybrid ESS of the EVs. It is showing the when the irradiation value change at time 1 sec then the ultra-capacitor controls the transient and maintains the required power at the constant label.

Fig. 14

Capacitor results.

Fig. 15

Power Demand.

To validate the finding of Simulink, the Hardware in the Loop (HIL) test is also performed on Typhoon HIL, 402 set up. Figure 16 shows the battery supply current The speed and torque of EV are displayed in Figs. 17 and 18 respectively. With these results, it can be concluded that the mathematical analysis is verified in simulations and validated in real-time using Hardware-in-the-Loop technology.

Fig. 16

Current through battery.

Fig. 17

Actual Speed of EV.

Fig. 18

Torque generated by EV.

6 Conclusion

Fuzzy Logic Controller is used to control split power management in between the SC and the battery, to provide power for the output of the BLDC E-rickshaw engine. Generally, traditional E-rikshaw runs roughly 50–60 km at one time. And the loading time is 7–8 hours. But it’s not very economical for a driver. In this solar-assisted method, E-rikshaw improves the run time, which increases the performance of e-rikshaw which is confirmed through simulation test, which shows the performance analysis of BLDC at different loading conditions. In a normal state, the battery is supplied to the engine to be powered, when the demand for power rises unexpectedly in a transient condition, in this case, the power demand is entirely met by the supercapacitor. This split power ratio protect the battery with a deep discharge and increases the battery life.

Footnotes

Acknowledgments

This research was funded by the collaborative research grant scheme (CRGS) project, Hardware-In-the-Loop (HIL) Lab, Department of Electrical Engineering, Aligarh Muslim University, India having project numbers CRGS/MOHD TARIQ/01 and CRGS/MOHD TARIQ/02.

The authors also acknowledge the technical support provided by the Hardware-In-the-Loop (HIL) Lab, Department of Electrical Engineering, Aligarh Muslim University, India.

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