Implementation of Optimal Energy Management of High Capacity Vehicles with Electrically Propelled Dolly Under Lateral Constraints using CasADi

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dc.contributor.authorJohannesson, Wilhelm
dc.contributor.authorLi, Ying
dc.contributor.departmentChalmers tekniska högskola / Institutionen för mekanik och maritima vetenskapersv
dc.contributor.examinerJacobson, Bengt
dc.contributor.supervisorGhandriz, Toheed
dc.date.accessioned2022-09-22T11:04:55Z
dc.date.available2022-09-22T11:04:55Z
dc.date.issued2022sv
dc.date.submitted2020
dc.description.abstractTo lower the environmental impact of road freight transport, high-capacity transport vehicles with electrically propelled dolly trailers (e-dollys) are proposed as a more efficient way of transportation. This distributed propulsion hybrid vehicle introduces challenges regarding lateral stability and new possibilities for energy management. In this thesis, these properties are addressed by a model predictive control (MPC) strategy. The thesis includes design of an optimal energy management MPC for a A-double truck with an e-dolly, using the optimization toolbox CasADi. The MPC controller finds the optimal speed, soc, internal combustion engine (ICE) gears, ICE propulsion, electric motor (EM) propulsion and retardation and braking. The MPC is designed using CasADis symbolic framework and sequential linear and quadratic programs (SLP) and (SQP), and IPOPT as optimization algorithms. The two dynamic models are: an explicit ordinary differential equation (ODE) describing the longitudinal dynamics and an implicit differential algebraic equation (DAE) describing both lateral and longitudinal dynamics. Discretization of explicit and implicit model dynamics is done with Runge-Kutta and IDAS numerical integration methods. A method for decoupling ICE gears from the mixed integer nonlinear program (MINLP) is designed and gear optimization is done with a one-step algorithm. A method for implementing online shrinking horizon as the truck is getting close to its destination is developed for the sequential programs. Two types of lateral stability constraints are tested, one rule based calculated speed limit, and one directly constraining states in the lateral dynamics model. The MPCs are evaluated with simulations and the fuel consumption is compared to a diesel truck. The MPC computation time is evaluated in respect to real time implementation. The two lateral stability constraints are evaluated. The MPC using SLP, and the rule based lateral stability constraint is determined to be fast enough to be implemented in real time but, the rule-based stability constraint is lacking and cannot guarantee lateral stability unless very conservative constraints are considered. The MPC including the nonlinear lateral dynamics is too computationally expensive to implement in real time for long horizons, but its optimal trajectories can serve as a benchmark for further simplifications of the lateral dynamics.sv
dc.identifier.coursecodeMMSX30sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/305654
dc.language.isoengsv
dc.relation.ispartofseries2022:63sv
dc.setspec.uppsokTechnology
dc.subjectModel predictive controlsv
dc.subjectoptimal energy managementsv
dc.subjectmotion controlsv
dc.subjectoptimizationsv
dc.subjectlateral stabilitysv
dc.subjectelectrified propulsionsv
dc.subjecthigh capacity transport vehiclessv
dc.subjectdistributed propulsion and simulationssv
dc.titleImplementation of Optimal Energy Management of High Capacity Vehicles with Electrically Propelled Dolly Under Lateral Constraints using CasADisv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
local.programmeSystems, control and mechatronics (MPSYS), MSc
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