Illustration of technician tuning a boost converter.

Boost Your Converter's Performance: Online Inductance and Capacitance Tuning

Soraya Malik in Tech & Innovation December 2025 • 4 min read.

"Discover how a novel algorithm can dynamically adjust your boost converter for peak efficiency, even with changing conditions."

In today's world, digital control of DC-DC converters has become a game-changer. Unlike older systems, these digitally-controlled converters aren't as easily thrown off by system noise or changes in component values. They're programmable, can use complex control strategies, and even allow for online updates. This adaptability makes them ideal for many applications.

Two main control methods dominate digital DC-DC converters: voltage mode control and current mode control. While voltage mode control is simple to design, it can be slow to respond to changes in voltage or load. Current mode control offers faster response times and wider bandwidth.

However, both methods rely on accurate modeling of the converter. Key parameters like inductance and output capacitance can drift over time due to temperature, aging, and load level. To maintain optimal performance, it's crucial to track these changes and adjust the converter accordingly. That’s where online inductance and capacitance identification comes in.

How Does the VFF-RLS Algorithm Fine-Tune Your Boost Converter?

Illustration of technician tuning a boost converter.

The Variable Forgetting Factor Recursive Least-Squares (VFF-RLS) algorithm offers a way to identify inductance and capacitance online in boost converters. This algorithm is designed to strike a balance between steady-state accuracy and the ability to track changing parameters. By continuously monitoring the system's error signal, it dynamically adjusts a 'forgetting factor,' optimizing the identification process.

Here’s a breakdown of the algorithm's key components:

Accurate Modeling: The algorithm relies on precise mathematical models of inductance and capacitance within the boost converter.
Recursive Least-Squares (RLS): RLS is a powerful adaptive filter known for its fast calculation speed and ability to converge quickly.
Variable Forgetting Factor: The forgetting factor determines how much weight is given to recent data versus past data. This factor is dynamically adjusted to maintain accuracy and responsiveness.
System Noise Recovery: By analyzing the error signal, the algorithm estimates and compensates for system noise, leading to more reliable identification.
Practical Implementation: The algorithm operates at a sampling rate only twice the switching frequency, making it suitable for low-cost applications.

The algorithm works by injecting a small pulse signal into the voltage reference, creating a dynamic process. Then, based on sampled data of input voltage, output voltage, and inductor current, inductance and capacitance are identified through the RLS algorithm. This approach ensures that the identification occurs in a dynamic state, allowing for continuous adjustment.

Real-World Validation

Experiments have confirmed that the VFF-RLS algorithm effectively tracks inductance and capacitance variations, demonstrating its potential for improving boost converter control performance. Its simplicity and low hardware requirements make it a practical solution for a wide range of applications. The research has been financially supported by the National Science Foundation of China.

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Everything You Need To Know

What are the primary advantages of digital control in DC-DC converters compared to older systems?

Digital control in DC-DC converters offers several key advantages over older systems. Primarily, they are far less susceptible to disruption from system noise and changes in component values. Furthermore, these digitally-controlled converters are programmable, enabling the use of complex control strategies. They also facilitate online updates, making them highly adaptable and suitable for a wide array of applications where flexibility and responsiveness are crucial.

What is the Variable Forgetting Factor Recursive Least-Squares (VFF-RLS) algorithm, and how does it optimize a boost converter?

The VFF-RLS algorithm is a sophisticated method used to identify inductance and capacitance online within boost converters. It intelligently balances steady-state accuracy with the ability to adapt to changing parameters. The algorithm dynamically adjusts a 'forgetting factor' based on the system's error signal, thereby optimizing the identification process. Key components include accurate modeling of inductance and capacitance, Recursive Least-Squares (RLS) for fast calculations, and the variable forgetting factor to balance responsiveness and accuracy. It also includes system noise recovery for more reliable identification.

What is the difference between voltage mode control and current mode control in digital DC-DC converters, and why does it matter?

In digital DC-DC converters, two main control methods are employed: voltage mode control and current mode control. Voltage mode control is simpler in design but tends to respond slowly to changes in voltage or load. In contrast, current mode control provides faster response times and wider bandwidth, making it more suitable for applications demanding quick adjustments. Both methods are dependent on accurate modeling of the converter's parameters such as Inductance and Output Capacitance, which can drift over time, influencing the overall performance.

How does the VFF-RLS algorithm identify inductance and capacitance in a boost converter in real-time?

The VFF-RLS algorithm identifies inductance and capacitance in a boost converter by injecting a small pulse signal into the voltage reference, creating a dynamic process. Using sampled data of input voltage, output voltage, and inductor current, the algorithm employs Recursive Least-Squares (RLS) to identify these parameters. This approach ensures that the identification occurs in a dynamic state, enabling continuous adjustment and optimization of the converter's performance in real-time. The algorithm operates at a sampling rate only twice the switching frequency, making it suitable for low-cost applications.

Why is online inductance and capacitance identification important for boost converter performance, and what are the implications of these parameters changing?

Online inductance and capacitance identification is crucial because key parameters like Inductance and Output Capacitance in a boost converter can change over time due to factors such as temperature, aging, and load level. These changes can lead to a degradation in the converter's performance, affecting its efficiency and reliability. By continuously tracking these changes using algorithms like VFF-RLS, the converter can be adjusted in real-time to maintain optimal performance, ensuring stability and extending the lifespan of the device. Failure to account for these drifts can lead to instability, reduced efficiency, and potential failure of the power electronics system.