Study Vehicle Battery Simulation and Monitoring System

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Figure 2. Charge and discharge curves for NiMH

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This model is implemented with blocks in Matlab / Simlink. It could also be done with an s-function in order to make it more flexible e.g. make it easier to change the equivalent circuit to a different one and to have multiple input/output ports. The drawback with this model is that it doesn’t take into account all the specific electrochemical features of the batteries but only the most common ones. For example it doesn’t models the hysteresis effects of the batteries. This is more essential in the Ni-MH technology. The hysteresis effect of the battery is shown in Figure 2 This effect shouldn’t be very hard to implement in the model, it is only to use one resistor for charge and another for discharge. The problem is to find the values of the 25 components. Fitting a curve by the “cut-and-try” principle could do it. However this isn't very accurate for different conditions. It is much better with values that are tested and measured at different SOC and temperatures. This is a big problem when modeling a chemical cell because all suppliers are very cautious with whom they are sharing their information. This is probably because of that the battery market is in a research era right now. Therefore it is very seldom that they supply any other than their customer with data of the battery (and sometimes not even them). This model was converted into a state space model in order to implement it into a vehicle simulation program called Advisor. The Battery block implements a generic dynamic model parameterized to represent most popular types of rechargeable batteries ^[7]. The equivalent circuit of the battery is shown Figures 3.

Figure 3. The equivalent circuit of the battery

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3.1. Lead-Acid Model

Discharge model (i* > 0)

(1)

Charge Model (i* < 0)

(2)

3.2. Lithium-Ion Model

Discharge Model (i* > 0)

(3)

Charge Model (i* < 0)

(4)

3.3. Nickel-Cadmium and Nickel-Metal-Hydride Model

Discharge Model (i* > 0)

(5)

Charge Model (i*< 0)

(6)

E_Batt = Nonlinear voltage (V)

E0 = Constant voltage (V)

Exp(s) = Exponential zone dynamics (V)

Sel(s) = Represents the battery mode. Sel(s) = 0 during battery discharge, Sel(s) = 1 during battery charging.

K = Polarization constant (Ah−1) or Polarization resistance (Ohms)

i* = Low frequency current dynamics (A)

i = Battery current (A)

it = Extracted capacity (Ah)

Q = Maximum battery capacity (Ah)

A = Exponential voltage (V)

B = Exponential capacity (Ah)−1 The parameters of the equivalent circuit as Figure 4 can be modified to represent a particular battery type, based on its discharge characteristics. A typical discharge curve is composed of three sections, as shown in the next figure:

Figure 4. Typical discharge characteristics

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The first section represents the exponential voltage drop when the battery is charged. Depending on the battery type, this area is more or less wide. The second section represents the charge that can be extracted from the battery until the voltage drops below the battery nominal voltage. Finally, the third section represents the total discharge of the battery, when the voltage drops rapidly ^[1]. When the battery current is negative, the battery will recharge following a charge characteristic as shown below Figure 5.

Figure 5. Typical charge characteristics

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The parameters of the model are deduced from discharge characteristics and assumed to be the same for charging. The Exp(s) transfer function represents the hysteresis phenomenon for the Lead-Acid, NiCD and NiMH batteries during charge and discharge cycles. The exponential voltage increases when battery is charging, no matter the SOC of the battery. When the battery is discharging, the exponential voltage decreases immediately shown Figure 6.

Figure 6. Exponential zone for lead –acid, NI-MH and NiCD

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3.4. Block Inputs and Outputs

The Simulink output of the block is a vector containing three signals. You can demulti plex these signals by using the Bus Selector block provided in the Simulink library.

4. Modelling and Simulation of Vehicle Nickel Hydrogen Battery (NiMH)

4.1. Model Validation

Experimental validation of the model shown a maximum error of 5% (when SOC is between 10% and 100%) for charge (current between 0 and 2C) and discharge (current between 0 and 5C) dynamics.

4.2. Model Assumptions

• The internal resistance is supposed constant during the charge and the discharge cycles and doesn't vary with the amplitude of the current.

• The parameters of the model are deduced from discharge characteristics and assumed to be the same for charging.

• The capacity of the battery doesn't change with the amplitude of current (No Peukert effect).

• The model doesn't take the temperature into account.

• The Self-Discharge of the battery is not represented. It can be represented by adding a large resistance in parallel with the battery terminals.

• The battery has no memory effect.

Limitations

• The minimum no-load battery voltage is 0 volt and the maximum battery voltage is equal to 2*E0.

• The minimum capacity of the battery is 0 Ah and the maximum capacity is Qmax.

4.3. The Simulation Produces the Followings Results

The power battery example illustrates a 200 volts, 6.5 Ah NiMH battery connected to a constant load of 50 A. The DC machine is connected in parallel with the load and operates at no load torque. When the State-Of-Charge (SOC) of the battery goes under 0.4 (40%), a negative load torque of 200 Nm is applied to the machine so it acts as a generator to recharge the battery. When the SOC goes over 80%, the load torque is removed so only the battery supplies the 50 amps load shown in Figure 6.

Figure 7. Simulation Model in SIMULINK for Vehicle nickel hydrogen battery (NiMH)

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5. Simulation Results

5.1. Description

The battery is connected to a constant load of 50 Amps. The DC machine is connected in parallel with the load and operates at no load torque. When the State-Of-Charge (SOC) of the battery goes under 0.4 (40%), a negative load torque of 200 Nm is applied to the machine so it acts as a generator to recharge the battery. When the SOC goes over 80%, the load torque is removed so only the battery supplies the 50 amps load. Battery voltage, SOC, Motor speed and Motor current signals are available at the output of the block Figure 7.

Figure 8. Description of Full Vehicle Simulation

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Figure 9. The simulation results

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5.2. Simulation

At t = 0 s, the DC machine is started with the battery power. The speed increases to 120 rad/s. The battery is also discharged by the constant DC load of 50 amps. At t = 280 s, the SOC drops under 40%. A mechanical torque of -200 Nm is applied to the machine so it acts as a generator and provides a current of 100 amps. Hence, 50 amps goes to the load and 50 amps goes to recharge the battery. At t = 500 s, the SOC goes over 80%. The mechanical torque is removed and the machine operates free. And the cycle restarts.

6. Battery Monitoring System Using Microcontroller

In this paper, the dynamic battery model that was used will be introduced and explored.

Figure 10. Measurement device and Voltage simulator

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The methodology utilized in modeling 12V lead-acid batteries will then be detailed. As all practitioners of battery engineering know, the equations and values provided by models have great variability. Data obtained from one battery test will yield parameters that may differ greatly from data obtained from a slightly different test. Therefore, exact methodology is very important to give end-users of battery models sufficient insight into the domain of their models and when they may no longer apply, and to compare variations in models. There are many models available for battery modeling, and a few of them are mentioned here in this section.

6.1. Experimental Methodology

The proposed model can therefore represent several types of discharge curves. It is now important to validate whether the obtained parameters properly represent the real behavior of a battery. There are several methods which can be used to validate the model. Of course, it is possible to validate the model by using other simulation models but the software containing these models is very rare and the parameters they require are sometimes difficult to obtain. The suggested validation approach consists of comparing directly (by superposition) the obtained discharge curves using the model with those of the manufacturers.

The experimental tasks for battery modeling involve placing current profiles upon the battery, and measuring voltage responses. The designed system as shown in Figure 9, Figure 10, Figure 11 and Figure 12 developed and it consists of Transformer, Micro controller, regulator, capacitor, LED, Monitor and power supply connected to each 12v battery unit. This unit collects all data regarding battery and sends it serially to microcontroller.

Figure 11. Experimental Hardware

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Figure 12. Electrical schematic for experimental setup

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Figure 13. Graph of current Vs Voltage

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Figure 14. Graph of discharge

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Figure 15. Graph of Charge

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