The rapid increase in the adoption of Solar Home Systems (SHS) in recent times hopes to ameliorate the global problem of energy poverty. The battery is a vital but usually the most expensive part of an SHS; owing to the least lifetime among other SHS components, it is also the first to fail. Estimating battery lifetime is a critical task for SHS design. However, it is also a complex task due to the reliance on experimental data or modelling cell level electrochemical phenomena for specific battery technologies and application use-case. Another challenge is that the existing electrochemical models are not application-specific to Solar Home Systems. This paper presents a practical, non-empirical battery lifetime estimation methodology specific to the application and the available candidate battery choices. An application-specific SHS simulation is carried out, and the battery activity is analyzed. A practical dynamic battery lifetime estimation method is introduced, which captures the fading capacity of the battery dynamically through every micro-cycle. This method was compared with an overall non-empirical battery lifetime estimation method, and the dynamic lifetime estimation method was found to be more conservative but practical. Cyclic ageing of the battery was thus quantified and the relative lifetimes of 4 battery technologies are compared, viz. Lead-acid gel, Flooded lead-acid, Nickel-Cadmium (NiCd), and Lithium Iron Phosphate (LiFePO₄) battery. For the same SHS use-case, State-of-Health (SOH) estimations from an empirical model for LiFePO₄ is compared with those obtained from the described methodology, and the results are found to be within 2.8%. The relevance of this work in an SHS application is demonstrated through a delicate balance between battery sizing and lifetime. Based on the intended application and battery manufacturer's data, the practical methodology described in this paper can potentially help SHS designers in estimating battery lifetimes and therefore making optimal SHS design choices.

The proliferation of Solar Home Systems (SHS) in recent times hopes to provide an alleviating solution to the global problem of energy poverty. Battery is usually the most expensive but important part of an SHS; it is also normally the first part to fail. Estimating the battery lifetime can help make informed system design choices, and it is therefore an important exercise for an SHS designer. Battery lifetime modelling is often a complex task requiring empirical data or reliance on modelling cell level electrochemical phenomena. This paper presents a simple battery lifetime estimation method specific to the application and candidate battery choices at hand. An SHS application specific simulation is carried out for a year and the effect of microcycles on the battery activity is analyzed. The concept of active Depth-of-Discharge (DOD) is introduced. Cyclic ageing of the battery is thus quantified and relative cycle lives of 2 battery technologies are compared. A delicate trade-off is demonstrated between battery sizing and lifetime. The described methodology is also compared with an empirical model and the lifetime results are found to be within 3.85%. The methodology described in this paper can potentially help SHS designers in making quick, reasonable estimations of battery lifetimes based on the intended application and battery manufacturer's data.