Topology optimization (TO) has become a powerful tool for generating lightweight structural designs. TO has been widely applied to linear static problems, where analytical sensitivities are easy to obtain. However, crashworthiness design requires nonlinear dynamic analysis, for which analytical sensitivities are generally not available. To extend TO into crash problems, approximation methods such as the Equivalent Static Load (ESL) method have been developed. ESL replaces the nonlinear problem with a series of linear static subproblems, ensuring that the displacement fields match at certain time steps. These subproblems can then be efficiently solved using standard TO techniques. A key limitation of ESL is that it relies on the initial mesh for all subproblems, which reduces accuracy for highly nonlinear crash responses. To address this, Triller proposed the difference-based ESL (DiESL) method, which updates the mesh in each subproblem to the deformed configuration, therefore improving approximation accuracy. However, existing DiESL implementations are restricted to single-material topology optimization (SMTO), where elements can be either solid or void. In contrast, multi-material topology optimization (MMTO) allows multiple material candidates per element, offering greater design freedom and the potential for better solutions. For crashworthiness applications, MMTO can leverage low-density materials (e.g., aluminum or magnesium) to form thick members that resist buckling, while using high-strength, high-density materials (e.g., steel) in critical stress regions to prevent yielding. By combining MMTO with DiESL, nonlinear crash performance can be further improved, offering a promising framework for lightweight and crashworthy structural design.