| 1. |
- Kang, Yuqiong, et al.
(författare)
-
Phosphorus-doped lithium- and manganese-rich layered oxide cathode material for fast charging lithium-ion batteries
- 2021
-
Ingår i: Journal of Energy Chemistry. - : Elsevier. - 2095-4956 .- 2096-885X. ; 62, s. 538-545
-
Tidskriftsartikel (refereegranskat)abstract
- Owing to their high theoretical specific capacity and low cost, lithium- and manganese-rich layered oxide (LMR) cathode materials are receiving increasing attention for application in lithium-ion batteries. However, poor lithium ion and electron transport kinetics plus side effects of anion and cation redox reactions hamper power performance and stability of the LMRs. In this study, LMR Li1.2Mn0.6Ni0.2O2 was modified by phosphorus (P)-doping to increase Li+ conductivity in the bulk material. This was achieved by increasing the interlayer spacing of the lithium layer, electron transport and structural stability, resulting in improvement of the rate and safety performance. P5+ doping increased the distance between the (003) crystal planes from ∼0.474 nm to 0.488 nm and enhanced the structural stability by forming strong covalent bonds with oxygen atoms, resulting in an improved rate performance (capacity retention from 38% to 50% at 0.05 C to 5 C) and thermal stability (50% heat release compared with pristine material). First-principles calculations showed the P-doping makes the transfer of excited electrons from the valence band to conduction band easier and P can form a strong covalent bond helping to stabilize material structure. Furthermore, the solid-state electrolyte modified P5+ doped LMR showed an improved cycle performance for up to 200 cycles with capacity retention of 90.5% and enhanced initial coulombic efficiency from 68.5% (pristine) or 81.7% (P-doped LMR) to 88.7%.
|
|
| 2. |
- Cheng, Lihong, et al.
(författare)
-
Model abstraction for discrete-event systems by binary linear programming with applications to manufacturing systems
- 2021
-
Ingår i: Science Progress. - : Sage Publications. - 0036-8504 .- 2047-7163. ; 104:3
-
Tidskriftsartikel (refereegranskat)abstract
- Model abstraction for finite state automata is helpful for decreasing computational complexity and improving comprehensibility for the verification and control synthesis of discrete-event systems (DES). Supremal quasi-congruence equivalence is an effective method for reducing the state space of DES and its effective algorithms based on graph theory have been developed. In this paper, a new method is proposed to convert the supremal quasi-congruence computation into a binary linear programming problem which can be solved by many powerful integer linear programming and satisfiability (SAT) solvers. Partitioning states to cosets is considered as allocating states to an unknown number of cosets and the requirement of finding the coarsest quasi-congruence is equivalent to using the least number of cosets. The novelty of this paper is to solve the optimal partitioning problem as an optimal state-to-coset allocation problem. The task of finding the coarsest quasi-congruence is equivalent to the objective of finding the least number of cosets. Then the problem can be solved by optimization methods, which are respectively implemented by mixed integer linear programming (MILP) in MATLAB and binary linear programming (BLP) in CPLEX. To reduce the computation time, the translation process is first optimized by introducing fewer decision variables and simplifying constraints in the programming problem. Second, the translation process formulates a few techniques of converting logic constraints on finite automata into binary linear constraints. These techniques will be helpful for other researchers exploiting integer linear programming and SAT solvers for solving partitioning or grouping problems. Third, the computational efficiency and correctness of the proposed method are verified by two different solvers. The proposed model abstraction approach is applied to simplify the large-scale supervisor model of a manufacturing system with five automated guided vehicles. The proposed method is not only a new solution for the coarsest quasi-congruence computation, but also provides us a more intuitive understanding of the quasi-congruence relation in the supervisory control theory. A future research direction is to apply more computationally efficient solvers to compute the optimal state-to-coset allocation problem.
|
|
| 3. |
- Feng, Lei, et al.
(författare)
-
Fuel Minimization of the Electric Engine CoolingSystem with Active Grille Shutter by IterativeQuadratic Programming
- 2020
-
Ingår i: IEEE Transactions on Vehicular Technology. - : IEEE. - 0018-9545 .- 1939-9359. ; 69:3, s. 2621-2635
-
Tidskriftsartikel (refereegranskat)abstract
- The electric engine cooling system with the active grille shutter requires intelligent and predictive control to reach its full benefits on fuel economy and thermal management. Conventional control methods regulate the coolant temperature to a fixed value but do not directly minimize the vehicle's fuel/energy consumption. By contrast, we design a fuel minimization controller through solving constraint nonlinear optimization problems, whose cost function is the total fuel consumption and constraints are the vehicle's physical limits. To achieve high computational efficiency and sufficient accuracy, the optimization problem is solved by iterative convex quadratic programming and quasilinearization. The advantages of the proposed control method on both fuel economy and engine thermal management are demonstrated by simulations.
|
|
| 4. |
- Guellouz, Safa, et al.
(författare)
-
Designing Efficient Reconfigurable Control Systems Using IEC61499 and Symbolic Model Checking
- 2019
-
Ingår i: IEEE Transactions on Automation Science and Engineering. - : IEEE. - 1545-5955 .- 1558-3783. ; 16:3, s. 1110-1124
-
Tidskriftsartikel (refereegranskat)abstract
- IEC 61499 provides a standardized approach for the development of distributed control systems. The standard introduces a component architecture, based on function blocks that are event-triggered components processing data and signals. However, it gives only limited support for the design of reconfigurable architectures. In particular, handling of several reconfiguration scenarios is quite heavy on this level since a scenario changes the execution model of the system due to requirements. To this end, a new IEC 61499-based model named reconfigurable function blocks (RFBs) is proposed. An RFB processes the reconfiguration events and switches directly to the suitable configuration using a hierarchical state machine model. The latter represents the reconfiguration model which reacts on changes in the environment in order to find an adequate reconfiguration scenario to be executed. Each scenario presents a particular sequence of algorithms, encapsulated in another execution control chart slave which represents the control model of an RFB. This hierarchy simplifies the design and separates the reconfiguration logic from control models. To verify its correctness and alleviate its state space explosion problem in model checking, this paper translates an RFB system automatically into a generalized model of reconfigurable timed net condition/event systems (GR-TNCES), a Petri net class that preserves the semantics of an RFB system. In this paper, along with verification of deterministic properties, we also propose to quantify and analyze some probabilistic properties. As a case study, we consider a smart-grid system, interpreting permanent faults in it as reconfiguration events, and we characterize them with the expected occurrence probability and the corresponding repair time. A tool chain ZiZo is developed to support the proposed approach.
|
|
| 5. |
- Liu, Junhui, et al.
(författare)
-
Optimal road grade design based on stochastic speed trajectories for minimising transportation energy consumption
- 2021
-
Ingår i: IET Intelligent Transport Systems. - : John Wiley & Sons. - 1751-956X .- 1751-9578. ; 15:11, s. 1414-1428
-
Tidskriftsartikel (refereegranskat)abstract
- Reducing energy consumption, regardless of fuel or electricity, of ground vehicles is a paramount pursuit in academia and industry. Current research concentrates exclusively on the improvement of the vehicle, but accepts the road conditions as external influences. The innovation of this article is to consider the road conditions, particularly the grade angle, as design variables. It is assumed that the stochastic speed trajectories of all vehicles on the road can be modelled by a Markov chain. The expected value of the average energy consumptions of all vehicles running on the road is defined as the objective function. The optimisation problem is solved by dynamic programming with Markov model. Evaluations have been made on both simulated and measured speed trajectories. For the simulated speed trajectories, the optimal road grade profile designed by the method saves up to 22% energy compared with a flat road. For the measured speed trajectories, the optimal road grade profile saves up to 2.7% transportation energy compared with the actual road profile. Application of this method on building road could lead to considerable energy saving.
|
|
| 6. |
- Liu, Junhui, et al.
(författare)
-
The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption
- 2017
-
Ingår i: Energies. - : MDPI AG. - 1996-1073. ; 10:5
-
Tidskriftsartikel (refereegranskat)abstract
- Reducing energy consumption of ground vehicles is a paramount pursuit in academia and industry. Even though the road infrastructural has a significant influence on vehicular fuel consumption, the majority of the R&D efforts are dedicated to improving vehicles. Little investigation has been made in the optimal design of the road infrastructure to minimize the total fuel consumption of all vehicles running on it. This paper focuses on this overlooked design problem and the design parameters of the optimal road infrastructure is the profile of road grade angle between two fixed points. We assume that all vehicles on the road follow a given acceleration profile between the two given points. The mean value of the energy consumptions of all vehicles running on the road is defined as the objective function. The optimization problem is solved both analytically by Pontryagin's minimum principle and numerically by dynamic programming. The two solutions agree well. A large number of Monte Carlo simulations show that the vehicles driving on the road with the optimal road grade consume up to 31.7% less energy than on a flat road. Finally, a rough cost analysis justifies the economic advantage of building the optimal road profile.
|
|
| 7. |
- Yang, Junjun, et al.
(författare)
-
A model-based deep reinforcement learning approach to the nonblocking coordination of modular supervisors of discrete event systems
- 2023
-
Ingår i: Information Sciences. - : Elsevier BV. - 0020-0255 .- 1872-6291. ; 630, s. 305-321
-
Tidskriftsartikel (refereegranskat)abstract
- Modular supervisory control may lead to conflicts among the modular supervisors for large-scale discrete event systems. The existing methods for ensuring nonblocking control of modular supervisors either exploit favorable structures in the system model to guarantee the nonblocking property of modular supervisors or employ hierarchical model abstraction methods for reducing the computational complexity of designing a nonblocking coordinator. The nonblocking modular control problem is, in general, NP-hard. This study integrates supervisory control theory and a model-based deep reinforcement learning method to synthesize a nonblocking coordinator for the modular supervisors. The deep reinforcement learning method significantly reduces the computational complexity by avoiding the computation of synchronization of multiple modular supervisors and the plant models. The supervisory control function is approximated by the deep neural network instead of a large-sized finite automaton. Furthermore, the proposed model-based deep reinforcement learning method is more efficient than the standard deep Q network algorithm.
|
|
| 8. |
- Yang, Junjun, et al.
(författare)
-
Reducing the Learning Time of Reinforcement Learning for the Supervisory Control of Discrete Event Systems
- 2023
-
Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 11, s. 59840-59853
-
Tidskriftsartikel (refereegranskat)abstract
- Reinforcement learning (RL) can obtain the supervisory controller for discrete-event systems modeled by finite automata and temporal logic. The published methods often have two limitations. First, a large number of training data are required to learn the RL controller. Second, the RL algorithms do not consider uncontrollable events, which are essential for supervisory control theory (SCT). To address the limitations, we first apply SCT to find the supervisors for the specifications modeled by automata. These supervisors remove illegal training data violating these specifications and hence reduce the exploration space of the RL algorithm. For the remaining specifications modeled by temporal logic, the RL algorithm is applied to search for the optimal control decision within the confined exploration space. Uncontrollable events are considered by the RL algorithm as uncertainties in the plant model. The proposed method can obtain a nonblocking supervisor for all specifications with less learning time than the published methods.
|
|
| 9. |
- Zhang, Huimin, et al.
(författare)
-
A learning-based synthesis approach to the supremal nonblocking supervisor of discrete-event systems
- 2018
-
Ingår i: IEEE Transactions on Automatic Control. - : IEEE. - 0018-9286 .- 1558-2523. ; 63:10, s. 3345-3360
-
Tidskriftsartikel (refereegranskat)abstract
- The paper presents a novel approach to synthesize supremal nonblocking supervisors of discrete-event systems (DES), when the automaton models of specifications are not available. Extending the L* learning algorithm, an S* algorithm is developed to infer a tentatively correct supervisor. If the tentatively correct supervisor is nonblocking, it is indeed the supremal nonblocking supervisor with respect to the plant and specifications. Otherwise, the blocking automaton is regarded as a new plant, and the specification is the nonblocking property. Then, the supremal nonblocking supervisor with respect to the new problem is computed using supervisory control theory of DES. Two simplification rules are introduced to the S* algorithm to decrease the computational cost. Finally, the S* algorithm is implemented based on the LearnLib framework, and experiments are performed to verify the proposed approach.
|
|
| 10. |
- Zhang, Huimin, et al.
(författare)
-
Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems
- 2019
-
Ingår i: IEEE Transactions on Automation Science and Engineering. - : IEEE. - 1545-5955 .- 1558-3783. ; , s. 1-14
-
Tidskriftsartikel (refereegranskat)abstract
- The paper presents an approach to the control of black-box embedded systems by integrating automaton learning and supervisory control theory (SCT) of discrete-event systems (DES), where automaton models of both the system and requirements are unavailable or hard to obtain. First, the system is tested against the requirements. If all the requirements are satisfied, no supervisor is needed and the process terminates. Otherwise, a supervisor is synthesized to enforce the system to satisfy the requirements. To apply SCT and automaton learning technologies efficiently, the system is abstracted to be a finite-discrete model. Then, a C* learning algorithm is proposed based on the classical L* algorithm to infer a Moore automaton describing both the behavior of the system and the conjunctive behavior of the system and the requirements. Subsequently, a supervisor for the system is derived from the learned Moore automaton and patched on the system. Finally, the controlled system is tested again to check the correctness of the supervisor. If the requirements are still not satisfied, a larger Moore automaton is learned and a refined supervisor is synthesized. The whole process iterates until the requirements hold in the controlled system. The effectiveness of the proposed approach is manifested through two realistic case studies.
|
|
