Charge planning and thermal management of battery electric vehicles

A Hamednia, V Hanson, J Zhao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
A Hamednia, V Hanson, J Zhao, N Murgovski, J Forsman, M Pourabdollah, V Larsson…
IEEE Transactions on Vehicular Technology, 2023ieeexplore.ieee.org
This article studies optimal thermal management and charging of a battery electric vehicle
driving over long-distance trips. The focus is on the potential benefits of including a heat
pump in the thermal management system for waste heat recovery, and charging point
planning, in a way to achieve optimality in time, energy, or their trade-off. An optimal control
problem is formulated, in which the objective function includes the energy delivered by the
charger (s), and the total charging time including the actual charging time and the detour …
This article studies optimal thermal management and charging of a battery electric vehicle driving over long-distance trips. The focus is on the potential benefits of including a heat pump in the thermal management system for waste heat recovery, and charging point planning, in a way to achieve optimality in time, energy, or their trade-off. An optimal control problem is formulated, in which the objective function includes the energy delivered by the charger(s), and the total charging time including the actual charging time and the detour time to and from the charging stop. To reduce the computational complexity, the formulated problem is then transformed into a hybrid dynamical system, where charging dynamics are modeled in the domain of normalized charging time. Driving dynamics can be modeled in either trip time or travel distance domains, as the vehicle speed is assumed to be known a priori, and the vehicle is only stopping at charging locations. Within the hybrid dynamical system, a binary variable is introduced for each charging location, in order to decide whether to use or skip a charger. This problem is solved numerically, and simulations are performed to evaluate the performance in terms of energy efficiency and time. The simulation results indicate that the time required for charging and total energy consumption are reduced up to and , respectively, by applying the proposed algorithm.
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