
During July 2025, Alex Bieswanger enhanced the Zewotherm Lambda integration within the evcc-io/evcc repository, focusing on improving energy accounting accuracy and deployment flexibility. He introduced a polarity parameter to handle negative excess energy values, adjusting the scaling logic to support more precise data processing across diverse Lambda deployments. Additionally, Alex made the integration port configurable, replacing the previously hardcoded value to simplify network configuration and onboarding. His work demonstrated practical application of Go, configuration management, and Modbus protocol expertise. The depth of these changes improved interoperability and reliability for Lambda-based charger integrations without addressing major bug fixes this period.
July 2025 — Zewotherm Lambda integration enhancements in evcc (evcc-io/evcc) delivered to improve energy accounting accuracy and deployment flexibility. Implemented handling for negative excess energy values via a new polarity parameter with corresponding scaling adjustments, and introduced configurable port support to replace the previous hardcoded value (default 502). No major bugs fixed this period. Impact: enables more accurate energy data processing across diverse Lambda deployments and simplifies network configuration, improving onboarding and reliability for Lambda-based charger integrations. Technologies demonstrated: Go-based Lambda integration, parameterization for energy polarity and scaling, and network/configuration management with traceable commits.
July 2025 — Zewotherm Lambda integration enhancements in evcc (evcc-io/evcc) delivered to improve energy accounting accuracy and deployment flexibility. Implemented handling for negative excess energy values via a new polarity parameter with corresponding scaling adjustments, and introduced configurable port support to replace the previous hardcoded value (default 502). No major bugs fixed this period. Impact: enables more accurate energy data processing across diverse Lambda deployments and simplifies network configuration, improving onboarding and reliability for Lambda-based charger integrations. Technologies demonstrated: Go-based Lambda integration, parameterization for energy polarity and scaling, and network/configuration management with traceable commits.

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