Abstract Functionally Graded Materials (FGMs) improve fatigue resistance in leaf springs subjected to cyclic loading by optimizing the distribution of material properties throughout the component, thus enhancing both performance and durability. These materials feature a gradual variation in composition and structure, enabling customized mechanical properties that better resist the stresses and strains encountered during repeated loading cycles. This study focuses on the design of a monoleaf spring composed of an FGM composite that combines carbon fiber–reinforced polymer with 50R steel, analyzed using finite element analysis (FEA). The investigation examines the spatial distribution of von Mises stress and strain energy across the thickness of the functionally graded monoleaf spring. Three different grading functions are employed: a straightforward power-law function (P-FGM), a modified symmetric power-law function (S–P-FGM), and a Sigmoid function (S-FGM). The parameter k in the power-law functions was varied (0.2, 0.5, 1, 2, 5 and 10) to understand its influence on stress distribution and strain energy. Results indicate that the spring’s performance improves with increasing k , with the highest value, k = 10, yielding the greatest strain energy storage capacity, making it ideal for applications demanding high energy absorption and resilience. Additionally, at k = 10, the FGM exhibits the highest margin of safety (MOS), reflecting superior strength and reliability. Among the functions tested, P-FGM and S–P-FGM provide the best results in terms of margin of safety and strain energy, while the S-FGM function performs the least effectively. Ultimately, the optimal design for a monoleaf spring is an FGM composite of carbon fiber–reinforced polymer and 50R steel with a power exponent k = 10, offering excellent strain energy capacity, strength, and safety margin, thereby significantly enhancing spring performance.
Hedia et al. (Mon,) studied this question.