Energy Management System for the Train Inspection Monorail

This master thesis addresses at the battery energy management of a battery powered vehicle; the Train Inspection Monorail or TIM. This work is an attempt at improving the autonomy of TIM but also at improving the reliability of its operation by using the energy stored in the battery in the smartest possible way. The main problem encountered with the previously existing solution was the lack of accuracy on the State-Of-Charge (SOC) estimation. In consequences the critical lower SOC limit is set to a relatively high value in order to avoid a break-down of the train in the middle of the tunnel, away from a charging station. Such a case would require a human intervention to make TIM operational again and this is not acceptable since it could require to postpone or stop the operation of the LHC. On another hand, the second main issue is the fact that the speed of the train is imposed by a controller which do not take into account the environment, the mission length and do not verify a priori if the energy remaining in the battery is sufficient to reach destination. This last task is currently ensured by the operator which could lead to appreciation error and to fully drained batteries before the end of the mission since the operator is not necessarily a trained expert. In the next parts of this document, it will be shown how these issue has been tackled by implementing a more accurate SOC estimation in order to know as accurately as possible the amount energy remaining in TIM batteries, a mechanical model targeting at providing an a priori estimation of the am unt of energy needed for mission completion and an nonlinear optimization system aiming at reducing the overall consumption of this train.