1. Introduction

2. Electric Vehicle Modelling

Figure 1. Battery-Electric vehicle model in AVL cruise.

Figure 1. Battery-Electric vehicle model in AVL cruise.

Designing of Motor and Battery

The propulsion unit of the vehicle delivers the force necessary to move the vehicle forward this force of the propulsion unit helps the vehicle to overcome the resisting forces like gravity, air and tire resistance.

To find the longitudinal performance characteristics of a car we need to consider first the forces acting on it while travelling in a straight line. The major external forces acting on a two-axle vehicle are:

• Aerodynamic resistance Ra
• Rolling resistance Rr of the front and rear tires Rrf and Rrr
• Drawbar load RD
• Grade resistance RG, (W sin θ)
• Tractive effort of the front and rear tires Ff and Fr (For a rear-wheel-drive vehicle, Ff = 0, whereas for a front-wheel vehicle, Fr = 0)

Figure 5. Free body diagram of vehicle.

Figure 5. Free body diagram of vehicle.

Total aerodynamic drag acting on the vehicle is given by:

$$F_{aero}=1/2\rho C_d{A}_f{V}^2$$

(2)

Where:

V = Vehicle Velocity

$\rho$ = Air Density

C_d = Drag Coefficient

A_f = Frontal Area

Rolling Resistance acting on vehicle due to tyre is composed primarily of

1. Resistance from tire deformation

2. Tire penetration and surface compression

3. Tire slippage & air circulation around wheel

4. Range of factors affect total rolling resistance

Total rolling resistance acting on the vehicle due to tyre is:

$$F_{rr}=mg{C}_{rr}$$

(3)

Total gradient resistance acting while climbing the slope is

$$F_{grade}=mg\sin \theta$$

(4)

Combination of all above forces will give us the total force acting on the vehicle at that constant speed.

Total Vehicular Resistance at Constant Velocity:

$$F_{tr}=F_{rr}+F_{ad}+F_{gr}$$

(5)

Power rating required by the motor can be given as:

$$\mathrm{Motor}\mathrm{Power}\mathrm{Required}=F_{tr}$$

(6)

Where V is Vehicle speed in m/s.

Battery Capacity

Range of electric vehicle based on the battery capacity is given by the relation:

Table 1. Vehicle Parameters.

Table 1. Vehicle Parameters.

VEHICLE PARAMETERS
Aerodynamic Drag Coefficient	0.38
Air Density	1.23
Front Area	2.1
Mass of Vehicle	2300
Rolling Resistance Coefficient	0.01
Wheel Radius	0.34
Accessory Load	600
Vehicle Speed	50kmph
Gear reduction Ratio	3.55

Table 2. Tractive force required to move vehicle.

Table 2. Tractive force required to move vehicle.

Gradient	Radian	Gradient Resistance(N)	Aerodynamic Drag(N)	Rolling Resistance(N)	Tractive Force (N)
0	0	0	96.19092	225.63	321.82092
1	0.0174444	393.5790377	96.19092	225.63	715.3999577
2	0.0348888	787.0383089	96.19092	225.63	1108.859229
3	0.0523333	1180.258084	96.19092	225.63	1502.079004
4	0.0697777	1573.118705	96.19092	225.63	1894.939625
5	0.0872222	1965.500624	96.19092	225.63	2287.321544
6	0.1046666	2357.28444	96.19092	225.63	2679.10536
7	0.1221111	2748.350933	96.19092	225.63	3070.171853
8	0.1395555	3138.581099	96.19092	225.63	3460.402019
9	0.157	3527.856192	96.19092	225.63	3849.677112
10	0.1744444	3916.057756	96.19092	225.63	4237.878676
11	0.1918888	4303.067659	96.19092	225.63	4624.888579
12	0.2093333	4688.768135	96.19092	225.63	5010.589055

Table 3. Battery Capacity required to propel the vehicle.

Table 3. Battery Capacity required to propel the vehicle.

Power(W)	Torque at Wheel (Nm)	Motor RPM Required	Motor Torque (Nm)	Accessory Load(W)	Battery Capacity (kWh)
4505.49288	17.23523379	686.4820798	4.854995434	600	7.65823932
10015.59941	38.31349909	686.4820798	10.79253495	600	15.92339911
15524.02921	59.38535025	686.4820798	16.72826768	600	24.18604381
21029.10605	80.44437509	686.4820798	22.66038735	600	32.44365908
26529.15475	101.4841653	686.4820798	28.58708883	600	40.69373212
32022.50162	122.4983185	686.4820798	34.5065686	600	48.93375243
37507.47505	143.4804401	686.4820798	40.41702538	600	57.16121257
42982.40594	164.4241451	686.4820798	46.3166606	600	65.37360891
48445.62827	185.3230604	686.4820798	52.203679	600	73.5684424
53895.47957	206.1708265	686.4820798	58.07628914	600	81.74321936
59330.30146	226.9610992	686.4820798	63.932704	600	89.89545219
64748.44011	247.6875522	686.4820798	69.77114146	600	98.02266016
70148.24677	268.3438783	686.4820798	75.58982487	600	106.1223702

Based on Table II and Table III calculation it is found that the capacity of battery re-quired is around 8 kWh on plain road when vehicle is running at a speed on 50 kmph. And that on the road with 12-degree gradient battery capacity required is equivalent to 100 kWh. But in actual road driving scenario we don’t drive at constant speed rather it depends on the driving condition due to which the theoretically calculated capacity is to high. Hence to determine the actual performance we simulate the vehicle model in AVL Cruise software or in MATLAB. We can consider the mean velocity of the driving cycle and calculate the power and capacity required using above calculations.

Motor selected is BLDC 2kW, 48V, 4200 RPM, 60Amps;

So, battery pack required would be 48V, 60Amps;

Cells in series = 48/3.7 = 13;

Cells in parallel = 60/2.5 = 24;

Total number of cells required = 37.

A Matlab model of a vehcle was developed to investigate the design and it is shown in Figure 6.

Figure 7 shows the state of charge as the time progresses. It also implies that the battery capacity available reduces as the time elapses.

Figure 8 Shows at all the points at which my motor is operating at. From Figure 8. we can understand that at a speed of 25-35 mph motor is operating a lot. Graph also helps to decide the size of the motor based on the working point distribution. If points are running out from the Torque line means we need to have larger motor for that particular drive cycle.

From the Figure 9 we can observe that the large quantity of battery power will be utilized at 50 to 80 kmph.

Worldwide harmonized Light vehicles Test Procedures used in the investigation is shown in Figure 11. It is the ideal cycle to determine the energy consumed by the vehicle. The power output, energy consumed and net torque developed by the vehicle under the WLTC cycle is shown in Figure 10. It shows the energy consumption data which is utilized to develope a battey management system.

Battey Management system using Matlab-Simulink: Battery performance is mainly dependent on the BMS. Battery management system (BMS) mainly helps to identify the state of charge, state of health and cell balancing during charging and discharging of the battery. In this model we have trying to adopt for different cell balancing that can be used in the BMS to increase the battery performance and life. Proper cell balancing helps to reduce cell degradation and hence increases the battery life. We have defined two techniques to check the performance of the battery pack. Optimization of balancing time is expected from these cell balancing techniques.

Passive Cell Balancing Technique

Passive balancing is the basic balancing techniques used earlier. It is the simplest balancing technique and uses additional load to balance the cells. Most common method of passive balancing is charge shuttling in which additional load (Resistor) is connected in parallel across each cell. Extra charge is dissipated in the form of heat through the shunt resistor connected in the parallel to the battery cell [24]. It cannot be used for lithium-based batteries as there is a high risk of explosion [25].

Figure 12. Passive Balancing circuit.

Figure 12. Passive Balancing circuit.

In state flow diagram, operations are carried out based on the current state of the system and based on the logic provided the system goes into the next state. This concept can be easily understood from the flow chart given in the Figure 13.

System will be continuously monitoring the state of charge and voltage of each cell within the battery pack. When in the difference between the maximum Voltage and the minimum Voltage is greater than 2% its assumed that cells are imbalanced and balancing protocol will be executed ad system will go into balancing state. Now the system will monitor Voltage of each cell and based on the logic provided it will arrange the cell in ascending order on their voltages. From the flow chart above let’s assume that cell 1 has the lowest voltage (or say SOC) in this case other two cells should be discharged unless and until their SOC is equivalent to the third cell (approximate Error of 2%). For this to happen system will ON the switch 2 and switch 3 which will connect cell 1 and cell3 to shunt resistor which is connected in parallel to cell. The resistor will discharge the cell by giving out charge in form of heat. Meanwhile system will keep checking the SOC difference once the difference is below 2% balancing sequence will stop and all the MOSFET will on OFF state.

Based on the control logic explained in Figure 13 a simulink model was developed in order to investigate the battery management system and it is shown in Figure 14. A battery subsystem of that simulink is separately shown if Figure 15.

3. Results and Discussion

Active Balancing Technique

In case of Active balancing charge from higher voltage cell is transferred to some active energy storage devices such as capacitor and inductor and then form active device to the lower voltage cell. The time required for this type of balancing technique is very less compared to that of passive balancing technique and also helps to have continuous charging hence increasing the battery life.

One such active balancing technique is switched capacitor active balancing technique.

Figure 17. Switched capacitor active balancing.

Figure 17. Switched capacitor active balancing.

In this shuffling of the charge is done between capacitor and the battery cells using pulse generator and MOSFET switch. Pulse generators are provided with a control logic to initiate the balancing sequence. When the SOC difference is above 2% the balancing sequence will initiate during which at MOSFET switching will take place at very high frequency. We will be using two pulse generators generating pulses with 50% phase delay due to which MOSFET will switch in an alternate form i.e. when on MOSFET is one other will be in the off condition. Due to this capacitor will get charged by first pulse generator and will get discharged when the second pulse generator is connected. Above process will continue till the SOC Drop is not below 2%. Once it is then the balancing sequence will terminate and regular charging cycle will continue. It has to be noted that during balancing sequence battery won’t be in charging state rather it will discharge the cell voltage and charge the cell with lower voltage.

Below relation will give the charge that is been stored in the capacitor and that is been transferred to the cell with lower voltage. Once each capacitor has reached its corresponding upper cell voltage (V_ui), the stored charge (Q_ci) for the i-capacitor is

$$Q_{C_i}=C_i{V}_{u_i}$$

(14)

Each switching cycle, the i-capacitor transfers the current I_ci from the most charged adjacent cell to the least charged adjacent cell according to

$$I_{C_i}=C_i(V_{u_i}-V_{l_i})f_{SW}$$

(15)

Where $V_{l_i}$ is the lower cell voltage of the i-capacitor, f_sw is the switching frequency.

Therefore, the capacitor behaves like a resistance and the equivalent resistance R_c is

$$R_c=\frac{V_{u_i}-V_{l_i}}{I_i}=\frac{1}{f_{SW}{C}_i}$$

(16)

By taking into account the on-resistance of the switches (Rsw), the total resistance for the i-capacitor (R_swi) is

$$R_{{SW}_i}=\frac{1}{f_{SW}{C}_i}+2\frac{R_{sw}}{D}$$

(17)

Where D is the duty cycle.

The efficiency degradation per capacitor follows

$$∆\eta =-\frac{{{(V}_{u_i}-V_{l_i})}^2}{R_{{SW}_i}}$$

(18)

Figure 18. Simulink model for switched capacitor system.

Figure 18. Simulink model for switched capacitor system.

Input form the pulse generator as shown in Figure 19. is given to MOSFET. Based on the requirement and balancing speed we can change the switching frequency using PWM-DC-DC-Converter.

The parameters and their values of balancing unit are provided in the Table 4 and the battery pack parametrs are shown in Table 5.

Figure 20. Control circuit.

Figure 20. Control circuit.

Switched capacitor balancing can also be termed as automatic balancing technique. Flow chart in Figure 22 gives us the basic idea about how the balancing takes place. Initially system will measure for the maximum and minimum SOC of each cell and it will get the difference between the maximum and minimum SOCs. If the difference is turned out to be more than 2% then charger will get disconnected and active balancing take place. MOSFET switches are connected in such a manner that if cell 1 discharges then cell 2 will get charged by the charge that is been discharged by the cell 1. Further the discharged charge is also stored in the capacitor connected in parallel across each pair of cells. Charge will be transferred to the cell with lower charge. The pulse generate will generate two type of pulses with 50% phase delay in the next pulse by doing so alternate switching will take place. This will continue unless charge is balanced in each of adjacent cells. Once the cells are balanced the charger will be connected and cycle will continue further.

Figure 21. Battery pack design.

Figure 21. Battery pack design.

Based on the results obtained it can be observed that the time required for cell balancing is around 140 seconds as seen in Figure 23. During cell balancing cell will undergo in discharge state unless the cells get balanced once they are balanced the cycle will to charging state.

4. Conclusions

• Balancing time required in case of passive balancing was 4500 seconds whereas that in case of active balancing was 140 seconds.
• Active balancing was continuous whereas passive balancing was not continuous and time taken at higher SOC is very high.
• Costing of passive balancing could be very high for larger battery pack and cost does not justify with the balancing time required.
• By adopting different active balancing techniques and different control logics we can further reduce the balancing time and hence increase the overall life and performance of the battery pack.

References

1. Emadi, Y l Lee, and K. Rajashekara, "Power electronics and motor drives in electric, hybrid electric, and plug-in hybrid electric vehicles," IEEE Trans. Ind. Electron, vol. 55. pp. 2237- 2245, June 2008. [CrossRef]
2. Stuart A., T. , and Zhu W., “Fast Equalization for Large Lithium-Ion Batteries”, IEEE Aerospace and Electronic Systems Magazine, Vol. 24, pp. 27-31, 2009. [CrossRef]
3. Zhang, X. , Liu P., and Wang D., “The Design and Implementation of Smart Battery Management System Balance Technology”, J. Convergence Information Technology, Vol. 6, No. 5, pp. 108-116, May 2011. [CrossRef]
4. Cao, J. , Schofield N., and Emadi A., “Battery balancing methods: A comprehensive review”, IEEE Vehicle Power and Propulsion Conf., VPPC08, pp. 1-6, 2008. [CrossRef]
5. Daowd, M. , Omar N., Van Den Bossche P., and Van Mierlo J., “Passive and active battery balancing comparison based on MATLAB simulation”, IEEE Vehicle Power and Propulsion Conf., VPPC 2011, pp. 1-7, 6-9 Sept. 2011. [CrossRef]
6. Kutkut N., H. , Wiegman H., Divan D. M. and Novotny D. W., “Design considerations for charge equalization of an electric vehicle battery system”, IEEE Trans. Industry Applications, 35(1), Jan. 1999. [CrossRef]
7. Moore, S. and Schneider, P., “A Review of Cell Equalization Methods for Lithium-Ion and Lithium Polymer Battery Systems,” SAE Technical Paper 2001-01-0959, 2001. [CrossRef]
8. West, S. , and Krein P. T., “Switched-Capacitor Systems for Battery Equalization”, IEEE Modern Techniques and Technology (MTT 2000). Proceedings of the VI International Scientific and Practical Conference of Students, Post-graduates and Young Scientists, pp. 5759, 2000. [CrossRef]
9. Pascual, C. , and Krein P. T., “Switched-Capacitor System for Automatic Series Battery Equalization”, IEEE Applied Power Electronics Conf. and Expo., pp. 848-854, 1997. [CrossRef]
10. Baughman A., C. , and Ferdowsi M., “Double-Tiered Switched- Capacitor Battery Charge Equalization Technique”, IEEE Trans. Industrial Electronics, Vol. 55. pp. 2277-2285, 2008. [CrossRef]
11. Sang-Hyun, P. , Tae-Sung K., Jin-Sik P., Gun-woo M., and Myung-Joong Y., “A New Battery Equalizer Based on Buck-boost Topology,” IEEE 7th Int'l Conf. Power Electronics, pp. 962-965, 2007. [CrossRef]
12. Cioroianu, Constantin Cristian, et al. "Simulation of an electric vehicle model on the new WLTC test cycle using AVL CRUISE software." IOP Conference Series: Materials Science and Engineering. Vol. 252. No. 1. IOP Publishing, 2017. [CrossRef]
13. Jin, Li-qiang, et al. "A study of novel regenerative braking system based on supercapacitor for electric vehicle driven by in-wheel motors." Advances in Mechanical Engineering 7.3 (2015). [CrossRef]
14. Ilimbetov, R. Yu, V. V. Popov, and A. G. Vozmilov. "Comparative Analysis of “NGTU–Electro” Electric Car Movement Processes Modeling in MATLAB Simulink and AVL Cruise Software." Procedia Engineering 129 (2015): 879-885.
15. Yang, Yajuan, Han Zhao, and Hao Jiang. "Drive train design and modeling of a parallel diesel hybrid electric bus based on AVL/Cruise." World Electric Vehicle Journal 4.1 (2010): 75-81. [CrossRef]
16. Iclodean, C. , et al. "Comparison of different battery types for electric vehicles." IOP conference series: materials science and engineering. Vol. 252. No. 1. IOP Publishing, 2017. [CrossRef]
17. Omariba, Zachary Bosire, Lijun Zhang, and Dongbai Sun. "Review of Battery Cell Balancing Methodologies for Optimizing Battery Pack Performance in Electric Vehicles." IEEE Access 7 (2019). [CrossRef]
18. Capron, J. Jaguemont, R. Gopalakrishnan, P. van dem Bossche, N. Omar, and J.vanMierlo, ‘‘Impact of the temperature in the evaluation of battery performances during long-term cycling–Characterisation and modelling,’’ Appl. Sci., vol. 8, no. 8, p. 1364, 2018. [CrossRef]
19. V. Mueller, R. Kaiser, S. Poller, D. Sauerteig, R. Schwarz, M. Wenger, V. R. H. Lorentz, and M. Maerz, ‘‘Introduction and application of formation methods based on serial-connected lithium-ion battery cells,’’ J. Energy Storage, vol. 14, pp. 56–61, Dec. 2017. [CrossRef]
20. J. Gallardo-Lozano, E. Romero-Cadaval, M. I. Milanes-Montero, and M. A. Guerrero-Martinez, ‘‘Battery equalization active methods,’’ J. Power Sources, vol. 246, pp. 934–949, Jan. 2014. [CrossRef]
21. Ye, Yuanmao, and Ka Wai Eric Cheng. "An automatic switched-capacitor cell balancing circuit for series-connected battery strings." Energies 9.3 (2016): 138. [CrossRef]
22. Kim, Moon-Young, et al. "Switched capacitor with a chain structure for cell-balancing of lithium-ion batteries." IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society. IEEE, 2012. [CrossRef]
23. Ye, Yuanmao, and Ka Wai Eric Cheng. "An automatic switched-capacitor cell balancing circuit for series-connected battery strings." Energies 9.3 (2016): 138. [CrossRef]
24. Manenti, A. , Abba, A., Geraci, A., & Savaresi, S. (2011). A new cell balancing architecture for Li-ion battery packs based on cell redundancy. IFAC Proceedings Volumes, 44(1), 12150-12155. [CrossRef]
25. Daowd, Mohamed, et al. "Battery management system-Balancing modularization based on a single switched capacitor and bi-directional DC/DC converter with the auxiliary battery." Energies 7.5 (2014): 2897-2937. [CrossRef]
26. A.R. Sibiceanu, A. Iorga, V. Nicolae, F. Ivan, Consideration on the Implications of the WLTC (Worldwide Harmonized Light-Duty Test Cycle) for a Middle-Class Car, CONAT Brașov ISSN 2069-0401, Transilvania University Press, pp 203-211, 2016.