Energy Management of Dual Energy Storage System with Average Current Mode Control for EV Applications

Balapanuru, Obulapathi; Lokhande, Makarand M.; Patnaik, Chinmay; Shah, Varsha A.

doi:10.1109/stpec49749.2020.9297722

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…As a result, the battery will not be overdischarged for any given driving cycle, as shown in Figure 3C. The proposed algorithm is a modified version presented in Obulapathi et al 11 It requires five inputs, namely, required total current from the two sources (

I_{D C^{*}}

), torque ( T ), and speed profile (

ω

) at the motor shaft, SOCs of battery, and UC as shown in Figure 4. From the DM perspective, the driving cycle has two modes of operation, namely, motoring and generating modes.…”

Section: Proposed Algorithm With Single Source Transition Capabilitymentioning

confidence: 99%

“…In addition, energy management algorithms (EMAs), control strategies, and configurations are also necessary to decide the distributed current/power from each source according to the driving conditions. [8][9][10][11] To draw the required current/power from the energy sources according to the control strategies and EMAs, PWM DC-DC converters with closed-loop control are necessary. Therefore, it is clear that a dual-energy storage system (DESS) performance with any given proposed algorithm depends on the closed-loop control of the PWM DC-DC boost converter.…”

Section: Introductionmentioning

confidence: 99%

“…In Demircali and Koroglu, 7 the performance of the Jaya optimization method is compared with that of dynamic programming, a global optimization method, and particle swarm optimization, another heuristic method for real‐time applications. In addition, energy management algorithms (EMAs), control strategies, and configurations are also necessary to decide the distributed current/power from each source according to the driving conditions 8–11 . To draw the required current/power from the energy sources according to the control strategies and EMAs, PWM DC‐DC converters with closed‐loop control are necessary.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Selection of power sharing factor for hybrid battery/ultracapacitor energy storage‐based EV through load emulation technique

Dhote,

Lokhande,

Balapanuru

2023

Circuit Theory & Apps

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The hybrid battery/ultracapacitor (UC) energy storage system for electric vehicles (EVs) proved more reliable and cost‐effective. Even with the best possible sizing of these energy storage devices, unforeseen EV loading cycles are causing a single‐source transition. Mainly, the UC exhaustion in acceleration or transient loading shifts the loading to the battery, causing overdischarge and reducing the life span. This paper presents a deterministic current control algorithm to restrict the maximum allowable battery discharge current. The current discharge control in the battery/UC is implemented using symmetrical carrier‐based digital average current mode (DACM). The proposed energy management algorithm (EMA) with variable battery current sharing factor typically controls the current flow between the battery and the UC so that the battery current is always within safe limits. The DC‐DC converter with proposed novel EMA allows the system to regulate the voltage and current flow between the two power sources. By sharing the currents in this way and limiting the battery current to a safe value, the system helps to prolong the battery's life and ensures that the vehicle operates safely and reliably over the long term. The EV load profile emulator provides the current sharing under dynamic operating conditions. The hardware results are supported to validate the single‐source transition under hybrid energy sources.

show abstract

I_{D C^{*}}

), torque ( T ), and speed profile (

ω

) at the motor shaft, SOCs of battery, and UC as shown in Figure 4. From the DM perspective, the driving cycle has two modes of operation, namely, motoring and generating modes.…”

Section: Proposed Algorithm With Single Source Transition Capabilitymentioning

confidence: 99%