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Resilient Composite Control for Stability Enhancement in EV Integrated DC Microgrids

Md Saiful Islam, Rahul Bhadani

TL;DR

This paper tackles stability challenges in EV-integrated DC microgrids that arise from CPL-induced negative impedance and low inertia by proposing a composite control framework. It integrates exact feedback linearization to Brunovsky canonical form, a virtual capacitor to emulate inertia, and a global integral terminal sliding mode backstepping controller with an improved fractional power reaching law to reduce chattering and accelerate convergence, with stability proven via Lyapunov analysis. The approach is validated through MATLAB/Simulink simulations under variable DC-bus references, fluctuating supply voltages, and time-varying control delays, showing substantial reductions in overshoot, undershoot, and settling time compared to a baseline sliding mode controller. The results indicate improved voltage regulation, robustness to disturbances, and potential for practical deployment in EV charging DC microgrids, with future work focusing on adaptivity, cyber-physical security, and AI-assisted parameter tuning.

Abstract

When electric vehicles (EVs) are integrated into standalone DC microgrids (DCMGs), stability issues arise due to their constant power load (CPL) behavior, which provides negative incremental impedance (NII). In addition, the microgrids suffer from an inherent low-inertia problem. Therefore, this study presents a composite controller incorporating a global integral terminal sliding mode controller with a backstepping controller. A virtual capacitor is employed to mitigate the low-inertia issue and strengthen the DC-bus response. An improved fractional power-based reaching law decreases chattering and accelerates convergence. Exact feedback linearization converts the nonlinear boost converter model into Brunovsky's canonical form, mitigating NII effects and non-minimum phase issues. The entire system stability is verified using Lyapunov control theory. Simulation outcomes confirm superior performance, with 34.4-53.3% reduction in overshoot, 52.9-74.9% in undershoot, and 12-47.4% in settling time compared to the existing controller.

Resilient Composite Control for Stability Enhancement in EV Integrated DC Microgrids

TL;DR

This paper tackles stability challenges in EV-integrated DC microgrids that arise from CPL-induced negative impedance and low inertia by proposing a composite control framework. It integrates exact feedback linearization to Brunovsky canonical form, a virtual capacitor to emulate inertia, and a global integral terminal sliding mode backstepping controller with an improved fractional power reaching law to reduce chattering and accelerate convergence, with stability proven via Lyapunov analysis. The approach is validated through MATLAB/Simulink simulations under variable DC-bus references, fluctuating supply voltages, and time-varying control delays, showing substantial reductions in overshoot, undershoot, and settling time compared to a baseline sliding mode controller. The results indicate improved voltage regulation, robustness to disturbances, and potential for practical deployment in EV charging DC microgrids, with future work focusing on adaptivity, cyber-physical security, and AI-assisted parameter tuning.

Abstract

When electric vehicles (EVs) are integrated into standalone DC microgrids (DCMGs), stability issues arise due to their constant power load (CPL) behavior, which provides negative incremental impedance (NII). In addition, the microgrids suffer from an inherent low-inertia problem. Therefore, this study presents a composite controller incorporating a global integral terminal sliding mode controller with a backstepping controller. A virtual capacitor is employed to mitigate the low-inertia issue and strengthen the DC-bus response. An improved fractional power-based reaching law decreases chattering and accelerates convergence. Exact feedback linearization converts the nonlinear boost converter model into Brunovsky's canonical form, mitigating NII effects and non-minimum phase issues. The entire system stability is verified using Lyapunov control theory. Simulation outcomes confirm superior performance, with 34.4-53.3% reduction in overshoot, 52.9-74.9% in undershoot, and 12-47.4% in settling time compared to the existing controller.
Paper Structure (12 sections, 33 equations, 5 figures, 3 tables)

This paper contains 12 sections, 33 equations, 5 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background
  3. Key Contributions
  4. Mathematical Modeling and Problem Formulation
  5. Proposed Controller Design
  6. Conversion to Canonical Form
  7. Design Framework for the Composite Controller
  8. Simulation Results and Discussion
  9. Scenario 1: Evaluation under varying DC-bus voltage reference
  10. Scenario 2: Evaluation under fluctuating supply voltage and time-varying control delay
  11. Conclusion and Future Perspectives
  12. Future Perspectives

Figures (5)

  • Figure 1: System schematic of the DC microgrid with electric vehicle integration.
  • Figure 2: Simplified circuit diagram of the DC microgrid with electric vehicle integration.
  • Figure 3: Block diagram of the proposed control strategy for the EV-integrated DCMG.
  • Figure 4: Dynamic response of the DC-bus voltage in scenario 1. At $t = 0$, the proposed GITSMBC reduces overshoot from $30\%$ to $14\%$, undershoot from $15\%$ to $4\%$, and settling time from $38$ ms to $20$ ms compared with ESMC. At $t = 0.54$ s, GITSMBC further improves performance with overshoot of $7\%$ (vs. $13.3\%$), undershoot of $0.67\%$ (vs. $2.67\%$), and settling time of $28$ ms (vs. $43$ ms).
  • Figure 5: Dynamic response of the DC-bus voltage in scenario 2. At $t = 0$, GITSMBC reduces overshoot from $30.5\%$ to $20\%$, undershoot from $17\%$ to $8\%$, and settling time from $25$ ms to $22$ ms compared with ESMC. At later ($t = 0.5$ s and $t = 1$ s), it maintains lower overshoot and undershoot with comparable settling times.