| 1. |
- Murgovski, Nikolce, 1980, et al.
(författare)
-
Convex relaxations in the optimal control of electrified vehicles
- 2015
-
Ingår i: American Control Conference. - 0743-1619. - 9781479986842 ; 2015-July, s. 2292-2298
-
Konferensbidrag (refereegranskat)abstract
- When controlling the energy flow in electrified powertrains by means of convex optimization, the typically non-convex set of the original formulation needs to be relaxed to a convex super-set. In this paper we show that when using the backward simulation approach, where vehicle velocity is equal to the reference velocity, the global optimum of the original non-convex problem can be obtained by solving the relaxed convex problem. When vehicle velocity is kept as a state in the problem, in the so called forward simulation approach, we provide a condition for which, when satisfied, an agreement will be achieved between the solutions of the relaxed and the original problem.
|
|
| 2. |
- Hu, Xiaosong, et al.
(författare)
-
Condition Monitoring in Advanced Battery Management Systems: Moving Horizon Estimation Using a Reduced Electrochemical Model
- 2018
-
Ingår i: IEEE/ASME Transactions on Mechatronics. - 1083-4435 .- 1941-014X. ; 23:1, s. 167-178
-
Tidskriftsartikel (refereegranskat)abstract
- Efficient battery condition monitoring is of particular importance in large-scale, high-performance, and safety-critical mechatronic systems, e.g., electrified vehicles and smart grid. This paper pursues a detailed assessment of optimization-driven moving horizon estimation (MHE) framework by means of a reduced electrochemical model. For state-of-charge estimation, the standard MHE and two variants in the framework are examined by a comprehensive consideration of accuracy, computational intensity, effect of horizon size, and fault tolerance. A comparison with common extended Kalman filtering and unscented Kalman filtering is also carried out. Then, the feasibility and performance are demonstrated for accessing internal battery states unavailable in equivalent circuit models, such as solid-phase surface concentration and electrolyte concentration. Ultimately, a multiscale MHE-type scheme is created for State-of-Health estimation. This study is the first known systematic investigation of MHE-type estimators applied to battery management.
|
|
| 3. |
- Basso, Rafael, 1979, et al.
(författare)
-
Traffic aware electric vehicle routing
- 2016
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil,November 1-4. ; , s. Art no 7795588, Pages 416-421
-
Konferensbidrag (refereegranskat)abstract
- Since the main constraint of electric vehicles is range due to limited battery capacity, the focus for routing these kind of vehicles should be energy consumption minimization. And since energy consumption depends on several aspects, this article introduces a new model for route optimization of Electric Commercial Vehicles, with a realistic energy consumption model based on factors such as road inclination, weight and speed. The main new feature is to consider average speed for the road network at different times during the day, with the vehicle adapting to traffic flow. Several experiments were performed to evaluate the impact of different elements in energy consumption. As a result a few topics are recommended for future work.
|
|
| 4. |
- Hu, Xiaosong, 1983, et al.
(författare)
-
Integrated optimization of battery sizing, charging, and power management in plug-in hybrid electric vehicles
- 2016
-
Ingår i: IEEE Transactions on Control Systems Technology. - 1063-6536 .- 1558-0865. ; 24:3, s. 1036-1043
-
Tidskriftsartikel (refereegranskat)abstract
- This brief presents an integrated optimization framework for battery sizing, charging, and on-road power management in plug-in hybrid electric vehicles. This framework utilizes convex programming to assess interactions between the three optimal design/control tasks. The objective is to minimize carbon dioxide (CO2) emissions, from the on-board internal combustion engine and grid generation plants providing electrical recharge power. The impacts of varying daily grid CO2 trajectories on both the optimal battery size and charging/power management algorithms are analyzed. We find that the level of grid CO2 emissions can significantly impact the nature of emission-optimal on-road power management. We also observe that the on-road power management strategy is the most important design task for minimizing emissions, through a variety of comparative studies.
|
|
| 5. |
- Johannesson, Lars, 1979, et al.
(författare)
-
Including a battery state of health model in the hev component sizing and optimal control problem
- 2013
-
Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - 1474-6670. - 9783902823434 ; , s. 398-403
-
Konferensbidrag (refereegranskat)abstract
- This paper studies convex optimization and modelling for component sizing and optimal energy management control of hybrid electric vehicles. The novelty in the paper is the modeling steps required to include a battery wear model into the convex optimization problem. The convex modeling steps are described for the example of battery sizing and simultaneous optimal control of a series hybrid electric bus driving along a perfectly known bus line. Using the proposed convex optimization method and battery wear model, the city bus example is used to study a relevant question: is it better to choose one large battery that is sized to survive the entire lifespan of the bus, or is it beneficial with several smaller replaceable batteries which could be operated at higher c-rates?
|
|
| 6. |
- Johannesson, Lars, 1979, et al.
(författare)
-
Predictive energy management of hybrid long-haul trucks
- 2015
-
Ingår i: Control Engineering Practice. - : Elsevier Ltd. - 0967-0661 .- 1873-6939. ; 41, s. 83-97
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel predictive control scheme for energy management in hybrid trucks that drive autonomously on the highway. The proposed scheme uses information from GPS together with information about the speed limits along the planned route to schedule the charging and discharging of the battery, the vehicle speed, the gear, and when to turn off the engine and drive electrically. The proposed control scheme divides the predictive control problem into three layers that operate with different update frequencies and prediction horizons. The top layer plans the kinetic and electric energy in a convex optimization problem. In order to avoid a mixed-integer problem, the gear and the switching decision between hybrid and pure electric mode are optimized in a lower layer in a dynamic program whereas the lowest control layer only reacts on the current state and available references. The benefits of the proposed predictive control scheme are shown by simulations between Frankfurt and Koblenz. The simulations show that the predictive control scheme is able to significantly reduce the mechanical braking, resulting in fuel reductions of 4% when allowing an over and under speed of 5. km/h
|
|
| 7. |
- Murgovski, Nikolce, 1980, et al.
(författare)
-
Combined design and control optimization of hybrid vehicles
- 2015
-
Ingår i: Handbook of Clean Energy Systems. - 9781118991978 ; , s. 1-14
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Hybrid vehicles play an important role in reducing energy consumption and pollutant emissions of ground transportation. The increased mechatronic system complexity, however, results in a heavy challenge for efficient component sizing and power coordination among multiple power sources. This chapter presents a convex programming framework for the combined design and control optimization of hybrid vehicles. An instructive and straightforward case study of design and energy control optimization for a fuel cell/supercapacitor hybrid bus is delineated to demonstrate the effectiveness and the computational advantage of the convex programming methodology. Convex modeling of key components in the fuel cell/supercapactior hybrid powertrain is introduced, while a pseudo code in CVX is also provided to elucidate how to practically implement the convex optimization. The generalization, applicability, and validity of the convex optimization framework are also discussed for various powertrain configurations (i.e., series, parallel, and series-parallel), different energy storage systems (e.g., battery, supercapacitor, and dual buffer), and advanced vehicular design and controller synthesis accounting for the battery thermal and aging conditions. The proposed methodology is an efficient tool that is valuable for researchers and engineers in the area of hybrid vehicles to address realistic optimal control problems.
|
|
| 8. |
- Murgovski, Nikolce, 1980, et al.
(författare)
-
Component sizing of a plug-in hybrid electric powertrain via convex optimization
- 2012
-
Ingår i: Mechatronics. - : Elsevier BV. - 0957-4158 .- 1873-4006. ; 22:1, s. 106-120
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel convex modeling approach which allows for a simultaneous optimization of battery size and energy management of a plug-in hybrid powertrain by solving a semidefinite convex problem. The studied powertrain belongs to a city bus which is driven along a perfectly known bus line with fixed charging infrastructure. The purpose of the paper is to present the convexifying methodology and validate the necessary approximations by comparing with results obtained by Dynamic Programming when using the original nonlinear, non-convex, mixed-integer models. The comparison clearly shows the importance of the gear and engine on/off decisions, and it also shows that the convex optimization and Dynamic Programming point toward similar battery size and operating cost when the same gear and engine on/off heuristics are used. The main conclusion in the paper is that due to the low computation time, the convex modeling approach enables optimization of problems with two or more state variables, e.g. allowing for thermal models of the components; or to include more sizing variables, e.g. sizing of the engine and the electric machine simultaneously.
|
|
| 9. |
- Murgovski, Nikolce, 1980, et al.
(författare)
-
Computationally efficient energy management of a planetary gear hybrid electric vehicle
- 2014
-
Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - : Elsevier BV. - 1474-6670. - 9783902823625 ; 19
-
Konferensbidrag (refereegranskat)abstract
- We present a method for obtaining a computationally efficient, sub-optimal energy management of an electrified vehicle containing a planetary gear set. We first reformulate the optimization problem to become separable in space (optimization variables). The problem is then decomposed into two optimization problems. The first is a static problem that looks for the optimal engine speed that maximizes efficiency of a compound unit, resembling an engine-generator unit combining the planetary gear and kinetic energy converters connected to it. The second is a dynamic optimization problem deciding the optimal power split between an electric buffer and the compound unit. By approximating the losses of the compound unit as convex, second order polynomial in generated power, we are able to solve the power split problem in less than 2 seconds, when the engine on/off sequence is known in advance. By comparing results with dynamic programming, we observed an approximation error of less than 0.2%.
|
|
| 10. |
- Murgovski, Nikolce, 1980, et al.
(författare)
-
Cooperative energy management of automated vehicles
- 2016
-
Ingår i: Control Engineering Practice. - : Elsevier BV. - 0967-0661 .- 1873-6939. ; 57, s. 84-98
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a cooperative adaptive cruise controller that controls vehicles along a planned route in a possibly hilly terrain, while keeping safe distances among the vehicles. The controller consists of two predictive layers that may operate with different update frequencies, horizon lengths and model abstractions. The top layer plans kinetic energy in a centralized manner by solving a quadratic program, whereas the bottom layer optimizes gear in a decentralized manner by solving a dynamic program. The efficiency of the proposed controller is shown through several case studies with different horizon lengths and number of vehicles in the platoon.
|
|
