How do inverter switching strategies influence battery health?

Traditionally, power converter design for energy storage systems (BESS) normally focuses on conversion efficiency and total harmonic distortion. In these designs, the battery is often modeled as a simple dc voltage source with fixed capacity and resistance.

However, when it comes to high-density BESS and electric vehicle architectures, the interaction between the inverter’s switching strategy and the battery’s electrochemical state constitutes a significant design factor. Research indicates that switching frequencies and modulation topologies influence the degradation mechanisms within Lithium-Ion cells. This leads to a need to examine how specific electrical control strategies affect battery longevity.

How does ripple frequency impact battery degradation?

For a given filter inductance, the current ripple is inversely proportional to the switching frequency. This means that higher frequencies make the ripple currents in the ac output waveform smaller.

The impact of ac ripple currents on battery health varies significantly with frequency. Data from recent studies indicate that low-frequency ripples, specifically those below 10 Hz, contribute more to capacity degradation than high-frequency switching ripples.

As shown in Figure 1, the data presents the degradation trends:

Low Frequency (<10 Hz): The period of the ac current is sufficient to affect electrochemical diffusion processes within the active materials. This results in micro-cycling of electrode particles, which may cause thermal stress and capacity loss. Therefore, low-frequency oscillation is detrimental to cell chemistry.
High Frequency (>1 kHz): At frequencies typical of modern semiconductor switching, the impedance of the battery is primarily determined by ohmic and inductive behaviors rather than by electrochemical charge transfer. So, high-frequency ripples lose less capacity than low-frequency oscillations, as long as the RMS amplitude is within rated limits.

Figure 1. Experimental validation of frequency-dependent battery aging. Note the divergence in capacity fade (d) between damaging low-frequency zones and benign high-frequency zones. (Image: IEEE)

Can higher switching frequencies improve system efficiency?

Though semiconductor switching losses generally increase with frequency, battery efficiency follows a different trend. Furthermore, in solid-state transformer applications using dual active bridge (DAB) topologies, higher switching frequencies can reduce losses within the energy storage element.

Research utilizing a vector fitting method to model Li-ion cells reveals that at high frequencies, the cell exhibits inductive behavior, indicating that its impedance characteristics change favorably.

As shown in Figure 2, the efficiency trade-offs are clear:

The top plot shows that battery efficiency increases from approximately 90% to 96% as the frequency rises from 16 kHz to 40 kHz. The inductive reactance at these frequencies limits the magnitude of the ripple current across the battery’s internal resistance.
However, the bottom plot indicates that DAB converter efficiency decreases as frequency rises. The analysis identifies an optimal operating point at which the combined system efficiency is maximized. In experimental setups, adjusting the frequency from 20 kHz to 22 kHz improved aggregate efficiency. Such a move optimizes the system holistically rather than isolating components.

How does active modulation balance battery health?

Figure 2. Efficiency trade-off between battery and converter losses at varying switching frequencies, highlighting an optimal operating point for overall system efficiency. (Image: University of Oviedo)

One of the challenges associated with inverters, such as cascaded H-bridge configurations, is that variations in cell aging can lead to pack imbalances. Normally, standard passive balancing methods dissipate excess energy as heat.

Using a PI controller, this method determines the switching sequence for battery cells. The controller assigns duty cycles based on a priority index derived from both State-of-Charge (SoC) and SoH. Figure 3 displays the results of this algorithm:

Plot A demonstrates the convergence of SoC levels under standard conditions.
Plot C illustrates a scenario with SoH variance (e.g., 900 cycles vs. 0 cycles). The controller detects the aged condition of the older battery and reduces its discharge rate relative to the newer cells.
Plot E shows that the system maintains synchronization under high load conditions. Additionally, it manages the discharge rates of individual cells without requiring external hardware balancing circuits.

Figure 3. Dynamic SoC balancing performance under varying load and health conditions. (Image: Wiley)

This approach shifts the balancing from a hardware problem to a software control problem, reducing component count while actively managing asset health.

Summary

Inverter control strategies directly impact the operational health of a BESS. Engineering designs that account for the frequency-dependent nature of battery impedance and utilize SoH-aware modulation can mitigate degradation mechanisms. Integrating these considerations into the control software and topology allows for improved management of battery assets.