Balancing Optimization and Implementation: A Critical Review of Energy Management Systems for Urban Electric Motorcycles

Sustainable urban development has driven the global adoption of light-duty electric vehicles, with electric motorcycles now prevalent in cities. Battery-electric powertrains show great potential for replacing internal-combustion engines; however, continuous stop-and-go driving causes high-frequency current transients, which induce stress and thermal degradation in the electric powertrain. Hybrid energy storage systems (HESSs), which integrate batteries and supercapacitors, are a well-established approach to mitigating these problems in EVs. However, their use in electric motorcycles is hindered by space, weight, and computational constraints. This paper surveys current approaches to studying and simulating energy storage, electric motors, power-conditioning elements, and connection topologies in EVs. Crucially, this review identifies a major limitation in existing research on light-duty electric vehicle powertrains: the widespread assumption that an advanced EMS requires high computational capacity, which remains largely incompatible with the low-power power-electronic control units (ECUs) in standard two-wheeled vehicles. To address these unresolved challenges, our critical analysis emphasizes the need to bridge theoretical optimization and hardware feasibility. From our perspective, future research must prioritize offline-to-online hybrid architectures that use edge computing and reduced-order models to deliver robust HESS performance within the strict spatial and computational constraints of modern electric motorcycles.