The problem of optimizing hardware cost under functional safety requirement is a desirable work for a safety-critical embedded application. The state-of-the-art algorithms called enhanced explorative hardware cost optimization (EEHCO) and simplified EEHCO (SEEHCO) have been used to study this problem for a distributed embedded application by iteratively removing some processors from opened processors (i.e., open-to-close). However, EEHCO has powerful cost optimization capability but inferior time efficiency, and vice versa for SEEHCO in large-scale heterogeneous distributed embedded systems. This study presents a price performance-driven hardware cost optimization (PPHCO) method, which is the combination of PPHCO1 and PPHCO2, to achieve powerful cost optimization capability and superior time efficiency simultaneously. PPHCO1 iteratively selects the processor with the maximum price performance to open and overcomes the inferior time efficiency (i.e., close-to-open). PPHCO2 iteratively selects the processor with the minimum price performance to close and further optimizes the hardware cost on the basis of PPHCO1 without losing time efficiency (i.e., open-to-close). Through significantly reducing the iteration count, PPHCO overcomes the inferior time efficiency of the open-to-close method. Through adopting union fast functional safety verification (UFFSV), PPHCO achieves powerful cost optimization capability. Experiments confirm that PPHCO not only achieves stronger cost optimization capability but also has better time efficiency than state-of-the-art EEHCO and SEEHCO algorithms.