Regulating the Heart Rate of Human-Electric Hybrid Vehicle Riders Under Energy Consumption Constraints Using an Optimal Control Approach

Electric bicycles are an emerging means of transportation. Especially people with physical limitations benefit from the added motor power to propel the bicycle. Conventional motor assistance strategies pose limits on the usability of these bicycles: they lack the flexibility to adapt to the individual physiological constitution of cyclists and do not properly manage the assist power over an entire trip. In this paper, we present a novel energy management system for human–electric hybrid vehicles that: 1) uses an optimal control approach to regulate the heart rate of the cyclist and 2) incorporates trip information to manage the motor assistance. The system consists of a control stage and a planning stage. In the control stage, a model predictive controller regulates the heart rate by changing the motor power and gear ratio to maintain a user-defined exertion while considering constraints. The planning stage processes a priori information about the user and the route to estimate the power demand during different sections of the trip and to calculate the optimal motor power for each section. Motor power constraints for each section are then formulated to limit the energy consumption and to save energy for those sections when motor power is most needed. We present simulation results to demonstrate that: 1) the combined control of motor power and transmission ratio is superior to using each control variable separately and 2) including a trip information helps to manage the energy consumption over the entire trip to decrease the risk of running out of energy. This system can help people with limited physical capabilities to safely engage in physical activity.