2014 IEEE International Conference on Electrical Engineering and Computer Science 24-25 November 2014, Bali, Indonesia
Battery Management System via Bus Network for Multi Battery Electric Vehicle Dwi Dharma Artakusuma, Hadha Afrisal, Adha Imam Cahyadi, Oyas Wahyunggoro MOLINA UGM - Department of Electrical Engineering and Information Technology Engineering Faculty, Universitas Gadjah Mada [email protected]
, [email protected]
, [email protected]
, [email protected]
always contributes the modification on rule of control system.
Abstract- This paper proposes multi-battery design of battery management control using bus communication method based on loop shaping. The experiment of proposed method shows that the capacity dynamics of battery has been improved. The multiple of battery control system is implemented in electric vehicle’s model, and we modify the origin control system using bus communication method auto tuning based on loop shaping. The result of modified control system using bus method based on loop shaping is shown in the implementation design response of battery management that the cost and reliability are improved. Moreover, this method could maintain the error steady state to be zero.
Previous research has been done on the control system of battery to establish serial or parallel connection between neighboring cells or to bypass a cell . And Enhanced and Efficient Battery maintenance , but nevertheless implement the approach on a real time system especially electric vehicle. This study conducts research on the development of auto-tuning multi-battery loop shaping using a gradient method. The advantage of gradient algorithm is that it has global stability properties. This algorithm is applied in Battery management model.
Keywords - Component; Battery Management; MultiBattery Design; Bus Communication System
BATTERY MANAGEMENT SYSTEM
A. Problem Description Battery Management System Battery management system divided into 4 problem states determining the health of battery. The states are battery capacity, cell balancing, load management, and battery cell life. Each state has different equation with common input.
INTRODUCTION (HEADING 1)
Nowadays, BMS (Battery Management System) is developed in various application. Battery has more favor than other energy source, in example vehicle namely UAV can be expand the work region when it builds connection and communication with other important point spots, especially manned aerial vehicle and satellite  include battery.
Battery capacity is the battery energy status which can calculate by SoC method. The SoC is defined as the present capacity of the battery expressed as a percentage of some reference. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC of battery in order to keep it safely being charged and discharged at a suitable level and to prolong the life cycle of the battery . However, the measurement of SoC always needs update because of the battery capacity change with aging (used) time.
Research on battery management system is one of the most attractive in the last decade. With the system it is possible to establish either serial or parallel connections between neighboring cells or to bypass a cell . The Battery management system experiment is most interesting because of its advantage that is it can be applied at dangerous area unreachable. The use of Battery management system may reduce the cost with the smart charge (discharge) load .
Cell balancing is the battery charge management to balance of battery capacity (if same specification), commonly to balance battery voltage so to prevent battery cell to charge with another cell when used parallel system. The battery cell itself can broken if the charge over rating the maximum battery specification. Besides it manage the charge of battery power source each cell.
There are several kinds of Battery management system, such as charge management, load management, over charge (discharge)  The researcher mostly use over charge (discharge) management, because this vehicle has more advantages than does fixed charge(discharge) battery management system. The other profits are that battery has small size and agile, has ability to removable easily and commonly same capacity with same specifications. Besides that, battery management system has low complexity mechanical system,
Load management is monitoring the batteries power usages and determining which plant use to improve battery reserve life. The decision is to make become important wisely especially electric vehicle which has high mobility and automatically work (manual with limited administrator).
The conditions of under-actuated system, multipleinput multiple-output (MIMO), and non-linier dynamics system in Batteries making the batteries is difficult and complicated to control . The complexity at battery control becomes a defiance to scientists so that battery experiment
Battery cell life is to measure how long battery life depend on battery capacity which each usage the capacity degrading equally time. The calculation is determined by
978-1-4799-8478-7/14/$31.00 ©2014 IEEE 179
balancing so the workload of main control can be minimize.
SoC, cell balancing, load management importantly the battery specification has different characteristic. Beside the 4 problem stages earlier, the major problem is when applied for establish serial or parallel connection between neighboring cells or to bypass a cell in electric vehicle. Reliability communication each battery, master decision, and less computing need to design and calculate so the system becomes reliable. That will the main focus this study conducts research on the development. III.
Before this chapter explains the methodology to solve multi battery in electric vehicle problem i.e. by enhancing the auto-tuning multi-battery loop shaping using a gradient method. The flowchart of the loop shaping using a gradient method (see Fig.1) will be described in the following lines.
Fig.2 Bus network Control When the number of battery cell is to many, the workload of control is high, so to solve the main issue of workload the semi autonomous slave control need. Slave control (Fig.2) is work with task job handle the measure and control of cell balance with supervisor of master control. The master control just need the data from slave control then calculate the best path instruction without nearly touch the equation (almost same with military command chain with the higher command chain the large army can control. The master control command is from slave control data sent continually with help of gradient algorithm. Gradient algorithm then give result to give point each point to easily the decision maker. Many techniques have been proposed previously to estimate the SoC of battery cells or battery packs, for the case of this study the approach of SoC using voltage based. i.e. the common battery at market use Lead Acid Battery and Li-Ion battery.
Figure 1. flowchart of bus network for multi battery Fig. 3 Relationship between Voltage and SoC of Lead Acid Battery
The algorithm begins with input the slave control number i.e. battery cell and slave control type. As shown in Fig. 2, the main control work semi autonomous to reduce computing and focus to maintenance and monitoring battery decision. The slave control is manage the algorithm of battery cell i.e. SoC algorithm and cell
When the battery is discharging, the voltage drops more or less linearly. for Lead Acid battery (fig 3) the voltage diminishes significantly but on the other hand for Li-Ion battery (fig. 4) the voltage diminishes is very small change .
by semi autonomous and gradient algorithm monitoring at master control. By using the proposed BMS, the utilization rate of discharge and multi scale for battery energy cell can be improved.
Calculate the SoC precision significantly affected by the current, temperature, discharge rate and the age of cell. for the multi- battery if the workload implied to main processor become burden itself, then the used design of multi command chain become usefull.
Finally, it should be noted that the proposed bus network module can also be applied for fault-tolerant designs and both voltage and capacity balancing. Interestingly, since all switches are available from multiply the hardware two or more battery balancing and measurement techniques can be simultaneously applied to the proposed battery management system to balance both voltage and capacity, It should be mentioned that the proposed Bus Network modules require high speed communication. The development of high speed communication network is being designed and fabricated REFERENCES 
Fig. 4 Relationship between voltage and SoC in LiIon battery
Cell balancing when implemented in small scale of battery the problem never rise. the cost of processor with large output handle still expensive than to multiply the module itself. for multiply itself need a chain command so the workload burden can be smallest
In the electric vehicle besides we conclude to maintain the battery cell itself, for battery reserve life we need manage the Load. the important of load management is to make sure the safety of humanity besides the cell. i.e. in electric vehicle the load management for light and environment is high priority than engine. especially the electric vehicle get the high mobility so the need of light and environment at top prior than the engine itself. IV.
Once the Bus network technology reaches to sufficiently higher power efficiency, the battery life cycle can be significantly increase with more accurate measure
H. Lee, S. Uav, and K. Aerospace, “Implementation of Collision Avoidance System Using TCAS II to UAVS Necessity of Collision Avoidance System On-Board Requirements Types of Collision Avoidance Sensors,” pp. 1– 9, 2005. Helling Florian,Götz Stefan, Weyh Thomas, " A Battery Modular Multilevel Management System (BM3) for electric vehicles and stationary energy storage systems", Power Electronics and Applications (EPE'14-ECCE Europe), 2014 16th European Conference on, DOI:10.1109/EPE.2014.6910821, Publication Year: 2014 , Page(s): 1 - 10. Chin-Long Wey ,Ping-Chang Jui,"A Unitized Charging and Discharging Smart Battery Management System", Connected Vehicles and Expo (ICCVE), 2013 International Conference on, DOI: 10.1109/ICCVE.2013.6799924, Publication Year:2013, Page(s): 903-909. Man, K.L.; Kaiyu Wam; Ting, T.O.; Chen. C; Krilavicius. T.; Chang. J.; Poon. S.H, "Towards a hybrid approach to SoC estimation for a smart Battery Management System(BMS) and battery supported Cyber-Physical Systems(CPS)", Future Internet Communications(BCFIC), 2012 2nd Baltic Congress on, DOI: 10.1109/BCFIC.2012.6217989, Publication Year:2012, Page(s):113-116 Cited by: papers(2) IEEE Conference Publications. Stukenberg. T.J.,"New methods for enchancedand efficiency battery maintenance",Telecommunications Energy Conference (INTLEC), 2012 IEEE 34th International, DOI: 10.1109/INTLEC.2012.6364476, Publication Year:2012, Page(s):1-4 IEEE Conference Publications.