Bidirectional Dc Dc Converter Matlab

European Journal Of Technique

journal homepage: https://dergipark.org.tr/en/pub/ejt

Matlab/Simulink Modeling Of Regenerative Recovery

Circuit with Bidirectional DC-DC Converter for Scooter

1. Introduction

Today, electric vehicles are used to reduce the increasing environmental pollution problems. Small and light electric vehicles (LEV) are preferred in large cities with dense population. Scooters are widely used in today's big cities as LEV. The range of electric vehicles is limited by their battery capacity. An electric vehicle with widely used batteries today has a shorter range. However, the battery charge time required for the electric vehicle to start again is quite high. In order to eliminate these disadvantages mentioned in electric vehicles, the energy in the battery should be used efficiently .

There are many methods used in the literature to increase the range of electric vehicles. Among these methods are increasing the efficiency of the electric motor, using different mechanical designs and using the regenerative braking method. These methods are used in all electric vehicles. In recent years, scooters have been widely used due to their practical use and the absence of traffic problems [4, 5].

Methods of optimizing electric motors and using different mechanical designs are the methods used to increase the range of scooters. However, the use of regenerative braking, which is one of these methods, is not preferred by the manufacturers in scooters that have a lot of use in urban transportation.

The purpose of the regenerative braking method is to transfer the energy produced in the electric motor during braking of the vehicle to the battery group. Thus, the vehicle has the opportunity to store a certain amount of an energy in the battery while driving. The energy is used again for the movement of the vehicle. Thus, the range value of the vehicle is increased.

The electric motors used in scooters are direct drive motors. The movement taken from the motor is designed without using any powertrain. Hereby, external rotor electric motors are preferred in scooters. The Brushless Direct Current Motor (BLDCM) is the most widely used in scooters. BLDCM controls are made with two methods, with and without sensors. In both methods, power electronic elements and microprocessor are used. The regenerative braking method used in BLDCM is unique to every electric vehicle. It is unique because of the power circuit components and software used .

Microprocessors suitable for Digital Signal Controller (dsPIC), Peripheral Interface Controller (PIC), Digital Signal Processing (DSP) and Sliding Mode Control (SMC) structure are used in sensor control algorithms. dsPICs are capable of stable, fast and high-resolution detection. In addition, it is preferred for regenerative control of electric motors used in electric vehicles, as it has special Pulse Width Modulation (PWM) channels for motor control [7, 8]. However, it is seen that the output of the microprocessor cannot provide sufficient current in the use of dsPIC. Therefore, motor driver

Accepted: Jul., 06. 2023

Scooter, which is in the class of light electric vehicles, is a very common transportation vehicle, especially in big cities. Brushless direct current motor (BLDCM) is preferred in scooters. These motors are a type of electric motor used in light electric vehicles (LEV) due to their features such as high efficiency, long operating life, high speed and silence operation. Although the BLDCMs used in the propulsion system of the scooter have high efficiency, they do not have a long range due to their limited battery capacity. The biggest problem with scooters is their short range. In order to solve this negativity, manufacturers are working on different solutions.

In this study, MATLAB/Simulink modelling of bidirectional DC-DC converter regenerative recovery circuit for scooter was carried out. It is aimed to increase the range with regenerative recovery. The system in the proposed study is implemented for a 300W BLDCM with a rated voltage of 24V. The effect of bidirectional DC-DC converter regenerative recovery is proven by MATLAB/Simulink results.

Research Article

integration is used between the processor and semiconductor power electronics elements . dsPIC needs the speed information obtained from the hall sensor and the data it receives from the current sensor in sensor control methods for system control . It is important to use SMC as a control algorithm in regenerative systems using PIC. The SMC algorithm assists in detecting the time variation of BLDCM resistance and inductance values with temperature or other factors . DSP is a special microprocessor that converts input signals from analog to digital and performs calculations on the signals more efficiently. One of the biggest advantages of DSP is that it allows system parameters to be easily changed to adapt to the application. Regenerative recovery circuits created with DSP are more complex than others. It has a more advanced architecture as software .

Sensorless Algorithms Are Based On The Back-Emf

principle. The zero crossing points of the back-EMF are obtained by comparing the phase at the section with the star point. In some regenerative recovery systems, the back-EMF method is not preferred due to the noise and error rate in the signal. The noise and error rate in the signal create high torque vibrations. Therefore, vector control is preferred in system control. DSP is generally preferred in applications performed with Field Oriented Control (FOC). When the control is performed with FOC, the control algorithm is complex and the processor load is high. In such applications, DSP is used even if the software is complex [13, 14].

Of

regenerative recovery circuit with bidirectional DC-DC converter for scooter is implemented. In the literature and applications, regenerative recovery system design has been found on the scooter, which is in the category of light electric vehicles. The outer rotor BLDCM used in electric scooters has been the focus of this study to fill this gap in the literature. In order for the BLDCM to work in the regenerative braking zone, the necessary control algorithm has been developed and the power electronics circuit has been modeled. The BLDCM used in the study has a rated power of 300 W, 24-36 V and a speed of 2120 rpm. Electronic circuit simulation was carried out with the LTspice software to determine the switching elements and other electronic elements that can be used in the driver circuit. The necessary algorithm for the control of the driver circuit and the test of this algorithm have been made.

The model of the system required for the regenerative recovery circuit and the transfer of the recovered energy to the battery was created with the MATLAB/Simulink software.

Recovery in scooters, which are frequently used in daily life, is an incomplete issue in the literature. In this study, the design of the bidirectional DC-DC converter regenerative recovery circuit, which is not included in the literature, has been realized.

2. Proposed System Model

The outer rotor BLDCM works in 4 zones. BLDCM needs to operate in the regenerative braking zone for regenerative state. These regions are shown in Figure 1. The first quarter is the forward acceleration zone. This is the quarter positive speed-positive torque situation. The second quarter is the reverse braking zone. This is the quarter negative speed- positive torque situation. The third quarter is the region of reverse acceleration. This is the quarter negative speed- negative torque situation. The fourth quarter is the forward braking zone. This quarter is the positive speed-negative torque situation . By changing the direction of the phase current in the regenerative braking region, a negative force is applied to the BLDCM. In this case, since the direction of the current is towards the battery, the mechanical energy of the motor can be stored as electrical energy.

Figure 1. Quadrants Of Operation Using A Bldcm

If the switching sequence is set to reverse the direction of the current, the BLDCM will operate in the braking zone. The force to be applied to the motor can be adjusted in the opposite direction by adjusting the PWM. The operating zone of the BLDCM is determined by controlling the switching signals.

This control is provided by the microprocessor. The signals received from the processor are transmitted to a driver circuit and transferred to the trigger terminals of the switching elements. The structure of the system is as in Figure 2.

Figure 2. System Flow Diagram

The BLDCM is powered by the DC bus voltage, but the current is controlled by commutation stage semiconductor switching elements. The commutation time is determined by the rotor position. Rotor position is detected differently in sensorless and sensored motors. In this study, since sensor control is preferred, rotor position is obtained with hall sensors. When permanent magnets on the rotor surface pass by the hall sensors, the position of the rotor is known by giving a 0-1 digital signal. The digital signal string is transmitted to the microcontroller. This data is compared with the reference speed with the control algorithm. According to the comparison result, the PWM signal is generated. The digital code sequence coming from the hall sensor changes according to the rotation direction of the motor. The microcontroller controls the bidirectional converter according to which quarter mode the BLDCM operates.

The truth tables for the operation of the motor operating zone and the regenerative braking zone are as in Tables 1 and 2 [9, 16].

2.1. Simulation Of Ltspice Circuit

The LTspice program was used to determine the current and voltage values and waveforms of the BLDCM driver of the proposed system. It is necessary to know the electrical characteristic Equation (1) of the motor for BLDCM driver design .

] (1)

where V is the voltage applied to the stator windings, e is the EMF formed in the stator windings, R is the phase winding resistance of a phase, i is the current passing through the winding, L is the stator winding inductance, M is mutual inductance and a, b, c phase windings.

The driver circuit designed with the LTspice program is shown in Figure 3. There are six IRF540N type MOSFETs in the inverter circuit. The drain-source voltage of this MOSFET is 100V and the continuous drain current is 33A. This MOSFET is suitable for fast switching as its input parasitic capacitance is low.

Figure 3. Ltspice Model Of Driver Circuit

BLDCM's back EMF waveform is designed as trapezoidal. There is a 60º phase difference between the trapezoidal waves seen in Figure 4.

Figure 4. Back Emf Voltages Of Phases A, B And C

The maximum and minimum values of the voltage depend on the speed of the motor and the voltage coefficient. Commutation is performed electronically in BLDCM. In the

Proposed Circuit, 120º Square Wave Commutation Is

implemented. Phase currents are shown in Figure 5. While the BLDCM phases are energized, the current passes through one phase and returns from another phase. In this case, there is no energy in the third phase. This process is carried out in accordance with a certain phase sequence and the movement of the motor is provided.

Figure 5. Phase currents A, B, C for 90% pulse width It was observed that the phase current increased when the percentage of pulse width increased. This means more braking torque. Equation 2 is used to calculate the braking torque and compare the torque produced at two different pulse widths .

(2)

where f is the frequency. e is the back EMF voltage of the phase, i is the phase current. a, b and c represent phases A, B and C. The electromagnetic torque produced by the BLDCM is as in Equation 3 .

⁄ )𝑖𝑐 (3)

where 𝐾𝑡 is torque constant and 𝜃𝑟 is the rotor angle. Braking torque is given by Equation 4 .

Deployment In Out-Of-Position Situations

D. Bendjaballah1, A. Bouchoucha1, M. L. Sahli1,2* and J-C. Gelin2

Abstract

Side-impact collisions represent the second greatest cause of fatality in motor vehicle accidents. Side-impact airbags have been installed in recent model year vehicle due to its effectiveness in reducing passengers’ injuries and fatality rates. In meeting these requirements, simulations of folding and deploying airbags are very useful and are widely used. The paper presents a simulation method for the deploying airbags using three materials in different working conditions. Finite element analysis is primarily used to evaluate this concept. In these simulations, the gas flow is described by the conservation laws of mass, momentum, and energy. The numerical results indicate that the FE method in this paper is capable of capturing airbag deploying process accurately.

Keywords: Airbag simulations, Out-of-position, Crash, Modeling, Out-of-position

Background

The passive safety of cars has become a very high prior- ity issue for the automotive industry. Today, there are not only one or two airbags in a car; certain models have ten times more than that. With the increasing usage of airbags, the number of accidents where the airbag itself can cause an injury to the occupant also increases

(Augenstein Et Al. 2003; Gabauer And Gabler 2010;

Audrey et al. 2011). As is well known, safety belts are also now devices designed to provide protection to the users of vehicles during crash events, minimizing the loads necessary to adapt their movement to the move- ment of the car (Freesmeier and Butler 1999; Schmitt et al. 1997). In general, the seat belt is designed to restrain the occupant in the vehicle and prevent the

Occupant From Having Harsh Contacts With Interior

surfaces of the vehicles. The airbag acts to cushion any impact with vehicle structure and has positive internal pressure, which can exert distributed restraining forces over the head and face. As a safety component of auto- mobile, an airbag decreases occupants’ injury likelihood effectively in case of an accident (Ruff et al. 2007). These safety elements can reduce the death rates on the roads, and its protection effects have been widely approved (Crandall et al. 2001; Teru and Ishikawa 2003). With computational tools such as finite element methods designed for dynamic contact problems, crashworthiness simulations can now be used with reliable accuracy to evaluate occupant protection in various collision condi- tions with safety metric/parameters such as acceleration, head injury criteria, intrusion distance, intrusion vel- ocity, and neck forces (neck injury risk or whiplash).

Thus, new types of airbag products are being developed to handle different collision scenarios.

Become Standard Equipment On Most New Passenger

vehicles (Braver and Kyrychenko 2004; Teng et al. 2007; Yoganandan et al. 2007). The airbag cushion is com- posed of a woven fabric which is rapidly inflated during a car crash. The airbag dissipates the passenger’s kinetic energy thereby reducing injury through biaxial stretching of the fabric bag and escaping gas through vents. There- fore, the performance of the airbag is greatly influenced by the mechanical properties of the fabric. Generally, air bags are designed to deploy in a crash that is equivalent to a vehicle crashing into a solid wall at 8 to 14 mph.

Air bags most often deploy when a vehicle collides with another vehicle or with a solid object like a tree. There are various types of airbags: frontal, side-impact, and curtain airbags. In general, the passenger side airbags are usually larger than the driver airbags (see Fig. 1).

Besançon, France

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Bendjaballah et al. International Journal of Mechanical

Doi 10.1186/S40712-016-0070-2

Extensive studies have shown that the airbag deploy- ment in load cases consists of two occupant loading phases: a punch-out effect where the airbag bursts out of its container with the airbag and airbag module cover accelerating towards the occupant and a second loading phase during which the airbag is taking on its deployed shape and volume (membrane-loading effect). Bankdak et al. (2002) developed an experimental airbag test system to study airbag-occupant interactions during close proximity deployment. The results provided insight for simulating the effect of inflation energy and mass flow on target response. Bedard et al. (2002) found that while left-side (driver-side) impacts accounted for only 13.5% of all crashes, the fatality rate among these

Crashes Was 68.3% In Comparison To Front Impact

(48.3%), right-side impact (31.3%), and rear impact (38.4%). These studies underscore the importance of oc- cupant safety during side-impact collisions. In the last years, the current market requested to reduce the time and cost airbag development. In order to achieve this result, virtual simulations play an important role since they allow to minimize the number of experimental tests (Pei et al. 2013; Cao et al. 2014). Several simulation models of airbag were established (Wang et al. 2007). It is feasible to optimize the parameters of airbag deploy- ment using simulation technology. Experimental and numerical studies have quantified injury risks to close- proximity occupants from deploying side airbags. These studies have focused on the prevention of the most ad- verse effects of airbag deployment (Duma et al. 2003).

Other studies have proposed airbag characteristics to minimize particular biomechanical responses (Haland and Pipkorn 1996). In a more recent study, Marklund and Nilsson (2003) compared deformation patterns with experimental data as well as the computational costs associated with three different airbag deployment simu- lation methods; they concluded that the SPH method is relatively inexpensive and produces incremental deform- ation patterns that compare most closely to the experi- mental results. The process of inflation of an airbag is one of the determining factors in saving lives. The duration from the initial impact of the crash to the full inflation of an airbag is about 40 ms, and during this time, the airbag goes from being in a folded state to a fully inflated state, with a high internal pressure. After achieving this state, the airbag begins to deflate, thus providing a nice cushion for the body impacting it.

Ideally, the person in the crash should come into contact with the airbag at this time. In the present study, a large volume passenger side airbag model is developed to handle different collision scenarios. The main aim is evaluate the performance of deploying of passenger side airbag using finite element methods (FEM).

Materials

The tensile specimens were made in different airbags (P: Peugeot, R: Renault, and VW: Volkswagen) with a length of 200 mm long and a width of 40 mm. Table 1 shows the mechanical properties of the airbag.

Tensile Tests

To determine the mechanical properties of the material of airbag used in the test pieces, tensile tests were performed on Lloyd EZ20 universal testing machine in Constantine. These tests were conducted using rect- angular samples. The axial force and axial displacement acquired during a test are converted into stress and the strain in order to be used for the fabric material model.

The continuous recording of the stress-strain data was performed during both the load and unload phases. A minimum of five samples were made in order to check the repeatability of the measurements. All the data was collected by using a PC-based data acquisition system and analyzed by commercial software. The picture frame test device that is made for this study is shown in Fig. 2.

Fig. 1 a Frontal and side airbags. b Oblique view of facet occupant model in sitting posture following airbag deployment (Lim et al. 2014)

0.150

Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

Page 2 Of 9

Figure 3 shows the stress-strain relationship of the airbag sample under axial tensile loads. The results are showing a linear increase in extension with the increas- ing stresses. This is an expected output and it confirms with the theoretical behavior of a sample subjected to tensile stress. The rupture strain values for different airbags (R/P/VW) were 0.322, 0.441, and 0.472, respect- ively. The measured elastic parameters (i.e., Young’s modulus E and initial yield strength) and Poisson’s ratio are summarized in Table 2. The tensile tests of the woven fabrics can show differences on mechanical prop- erties because woven fabrics can resist in-plane shear loads once the yarn lock-up angle has been reached. The differences of material property on material direction can affect the shape of fully deployed bag (see Fig. 3b).

Theoretical Background

Numerical simulations of airbags use very complex and techniques such as an orthotropic model to identify the mechanical behaviors during the airbag inflation and the fluid mechanics (gas flow) to describe the inflator gas flow (pressure gradient) and improve the representation of the pressures within the airbag. To model the airbag as an orthotropic model, three material constants have to be provided. Assuming a plane stress condition, the

Ð1Þ

where σ is the normal stress and τ is the shear stress, the subscript refers to the principal material directions, i.e., the fill and warp directions. Also, ε and γ are the strain components. The material elastic constants Qij are

Ð2Þ

where E1 and E2 are the Young’s modulus in the fill and wrap directions and G12 is the shear modulus of the fabric material. νij is the Poisson ratio of the material.

The gas exerts a pressure load on the airbag causing it to expand. This expansion puts the airbag under tensile stress lowering the expansion rate. In this study, heat conduction and heat transfer is not taken into account.

Fig. 2 A photograph of Lloyd EZ20 universal testing Fig. 3 Stress versus strain using Lloyd EZ20 machine for a three different airbags at 0° and 90° and b VW airbag test specimens at

Different Angles

Table 2 Physical and mechanical properties of the airbag

Page 3 Of 9

In the deployment of an airbag, an inflator supplies high velocity gas into an airbag causing it to expand rapidly. The gas inside the airbag is assumed to be ideal, to be of constant entropy, and to satisfy the equation of state:

Ð3Þ

Here p, ρ, and e are respectively the pressure, density, and specific internal energy, and γ is the ratio of the heat capacities of the gas. The gas flow is described by the conservation laws for mass, momentum, and energy that

Ð4Þ

here, V is a volume, A is the boundary of this volume,

N Is The Normal Vector Along The Surface A, And U

denotes the velocity vector in the volume. Applying Bernoulli’s equation in the case of an ideal gas with

Ð5Þ

Here, the subscript ex denotes quantities at the throat of the tube. Furthermore u, p, and ρ denote the quan- tities inside that part of the tube that is supplying mass.

Materials And Boundary Conditions

The airbag system mainly consists of three parts: the airbag itself, the inflator unit, and the crash sensor or diagnostic unit. Thus, to study the behavior of the airbag using FE simulations, we need to have an FE model of the airbag in the folded position. A FE model of the airbag was used to simulate the test condition as shown in Fig. 5. LS-DYNA® material model FABRIC (MAT_34) is used to simulate the airbag material. It is a variation of the layered orthotropic material model. Additionally, in the LS-DYNA® material model, fabric leakage can be accounted for. However, for this CAB material, the leak- age is almost negligible and therefore no leakage is specified. The mechanical properties can be determined from the physical test. Typical material properties for airbag fabrics are taken as given in Chawla et al. (2004a) (Table 3). These properties are used to simulate inflation process of airbag (see Table 1). The car dashboard is modeled as the rectangular thin plate using a MAT_RI-

Gid Material, And The Degrees Of Freedom Are Con-

strained in all the directions. The similar properties of thermoplastic polymer are assigned for contact purposes. The porosity of the fabric is assumed zero. The nitro- gen gas is taken for inflating the airbag. Properties of nitrogen gas and initial bag conditions are shown in Table 4. The example on which we perform the study is a typical passenger side airbag. The geometric de- tails have been measured from a commercially avail- able airbag. The initial state of the airbag is a closed rectangular whose sides are to be finished to 482 × 635 mm2 and is shown in Fig. 4.

Table 3 Material properties of airbag and rigid plate used in FE

–

Table 4 Initial values used for FE simulation of the swelling of

3.33 × 10−4

Fig. 4 The initial airbag geometry in the form of a rectangular Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

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