Many studies have shown that energy consumption of on-chip memory is a critical issue for multicore embedded systems. In order to reduce energy consumption, scratchpad memory (SPM), a software controlled on-chip memory, has been increasingly used. In a typical multicore embedded system that uses SPM in the on-chip memory, each core has local SPM and can access data in both local SPM and SPMs of other cores (i.e., remote SPM). Since the latency and energy of accessing remote SPMs is higher than accessing local SPM, how data are allocated in local and remote SPMs influences the performance and energy consumption of the system. This paper proposes a requirement-aware online hybrid on-chip memory management (ROHOM) method. This method contains an SPM supervisor that determines the SPM allocation of each task according to the dynamic access behavior and SPM requirements of the task. In addition, two policies: 1) free remote SPM space first and 2) get local SPM space first, are proposed in ROHOM to reduce the access frequency of remote SPMs. The experimental results show ROHOM can reduce energy delay product up to 69% (42% on average) in an 8-core system and up to 69% (50% on average) in a 16-core system when compared to a contention aware SPM allocation method. The hardware area overhead is insignificant (about 1.8%).