Energy Efficient Longitudinal Control
Licentiate thesis, 2018
The work considers controlling the drivetrain actuators more efficiently in a vehicle with predictive information. For this, dynamic programming is used to optimize engine speed trajectories during depletion mode for a series hybrid drivetrain. The result shows that choice of state and control signals has a direct impact on the engine speed trajectory and thereby the fuel consumption. Up to 21 % lower fuel consumption could be achieved for a series hybrid drivetrain compared to a rule based engine speed demand controller (along the best efficiency line) for the drivecycle analyzed. For a parallel hybrid drivetrain a DP method was compared to a heuristic strategy in order to determine the optimal discharge rate of the battery. In the simulation study done the DP method provided the best fuel consumption results. During evaluation of the physical tests the pre-optimized DP parameter set performed worse than the heuristic strategy. In the rig tests a fuel consumption reduction of 8 % was measured with the heuristic method, compared to a non predictive controller strategy. The DP algorithm provided 4 % reduction of fuel compared to a non predictive controller.
The work has also considered different modeling methods of a high voltage battery from recorded fleet data. One individual vehicle recorded battery pack current and voltage for one year. The recorded data was used to identify battery parameters for electric equivalent circuits. The measured current was used to calculate a reference voltage from the circuit equivalent parameters that was compared to the measured voltage. The best result was obtained for a single RC circuit model which obtained the highest average goodness of fit in voltage for the entire training data set.
Hybrid drivetrain control
Chalmers, Mechanics and Maritime Sciences (M2), Combustion and Propulsion Systems
Comparing Dynamic Programming Optimal Control Strategies for a Series Hybrid Drivetrain
SAE Technical Papers,; Vol. 2017-October(2017)
An Evaluation of Discharge Strategies for Plug-In Hybrid Electric Vehicles
25th Aachen Colloquium,; (2016)
Other conference contribution
Battery parameter estimation from recorded fleet data
SAE Technical Papers,; Vol. 2016-Octobeer(2016)
Areas of Advance
Other Electrical Engineering, Electronic Engineering, Information Engineering
Opponent: Jonas Mårtensson KTH