Browsing by Author "Longo, Stefano"
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Item Open Access An accelerometer based-feedback technique for improving dynamic performance of a machine tool(European Society for Precision Engineering and Nanotechnology, 2016-06-30) Abir, Jonathan; Morantz, Paul; Longo, Stefano; Shore, PaulA novel concept for improving machine dynamic performance was developed and realised, a virtual metrology frame, for a small size CNC machine with flexible frame. Its implementation in a simplified linear motion system shows a reduction in the magnitude of the first resonance in the plant frequency response function by 12 dB. Realising the concept required developing a real -time accelerometer-based measurement technique. It shows a low sensor noise σ=30 nm with optimal phase delay of <70 μs.Item Open Access Accuracy versus simplicity in online battery model identification(IEEE, 2016-09-22) Fotouhi, Abbas; Auger, Daniel J.; Propp, Karsten; Longo, StefanoThis paper presents a framework for battery modeling in online, real-time applications where accuracy is important but speed is the key. The framework allows users to select model structures with the smallest number of parameters that is consistent with the accuracy requirements of the target application. The tradeoff between accuracy and speed in a battery model identification process is explored using different model structures and parameter-fitting algorithms. Pareto optimal sets are obtained, allowing a designer to select an appropriate compromise between accuracy and speed. In order to get a clearer understanding of the battery model identification problem, “identification surfaces” are presented. As an outcome of the battery identification surfaces, a new analytical solution is derived for battery model identification using a closed-form formula to obtain a battery’s ohmic resistance and open circuit voltage from measurement data. This analytical solution is used as a benchmark for comparison of other fitting algorithms and it is also used in its own right in a practical scenario for state-of-charge estimation. A simulation study is performed to demonstrate the effectiveness of the proposed framework and the simulation results are verified by conducting experimental tests on a small NiMH battery pack.Item Open Access Chapter 192: Integration of torque blending and slip control using nonlinear model predictive control(Unknown, 2016-09-30) Basrah, M. Sofian; Siampis, Efstathios; Velenis, Efstathios; Cao, Dongpu; Longo, StefanoAntilock Braking System (ABS) is an important active safety feature in preventing accidents during emergency braking. Electrified vehicles which include both hydraulic and regenerative braking systems provide the opportunity to implement brake torque blending during slip control operation. This study evaluates the design and implementation of a new torque allocation algorithm using a Nonlinear Model Predictive Control (NMPC) strategy that can run in real-time, with results showing that wheel-locking can be prevented while also permitting for energy recuperation.Item Open Access Comparative analysis of forward-facing models vs backward-facing models in powertrain component sizing(Institution of Engineering and Technology, 2013-11-11) Mohan, Ganesh; Assadian, Francis; Longo, StefanoPowertrain size optimisation based on vehicle class and usage profile is advantageous for reducing emissions. Backward-facing powertrain models, which incorporate scalable powertrain components, have often been used for this purpose. However, due to their quasi-static nature, backward-facing models give very limited information about the limits of the system and drivability of the vehicle. This makes it difficult for control system development and implementation in hardware-in-the-loop (HIL) test systems. This paper investigates the viability of using forward-facing models in the context of powertrain component sizing optimisation. The vehicle model used in this investigation features a conventional powertrain with an internal combustion engine, clutch, manual transmission, and final drive. Simulations that were carried out have indicated that there is minimal effect on the optimal cost with regards to variations in the driver model sensitivity. This opens up the possibility of using forward-facing models for the purpose of powertrain component sizing.Item Open Access Constrained LQR for Low-Precision Data Representation(Elsevier Science B.V., Amsterdam., 2014-01-24T00:00:00Z) Longo, Stefano; Kerrigan, Eric C.; Constantinides, George A.Performing computations with a low-bit number representation results in a faster implementation that uses less silicon, and hence allows an algorithm to be implemented in smaller and cheaper processors without loss of performance. We propose a novel formulation to efficiently exploit the low (or non-standard) precision number representation of some computer architectures when computing the solution to constrained LQR problems, such as those that arise in predictive control. The main idea is to include suitably-defined decision variables in the quadratic program, in addition to the states and the inputs, to allow for smaller roundoff errors in the solver. This enables one to trade off the number of bits used for data representation against speed and/or hardware resources, so that smaller numerical errors can be achieved for the same number of bits (same silicon area). Because of data dependencies, the algorithm complexity, in terms of computation time and hardware resources, does not necessarily increase despite the larger number of decision variables. Examples show that a 10-fold reduction in hardware resources is possible compared to using double precision floating point, without loss of closed-loop performance.Item Open Access Control for motion sickness minimisation in autonomous vehicles.(Cranfield University, 2021-06) Htike, Zaw Lin; Longo, Stefano; Velenis, EfstathiosAutomated vehicles are expected to push towards the evolution of transportation systems and exploit the use of vehicular technologies. This thesis investigates the fundamentals of motion planning for minimising motion sickness in transportation systems of higher automation levels. The optimum velocity pro le is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimise the motion sickness and the journey time. Motion sick- ness is minimised by taking the optimum trajectory and velocity profile for any given road path generated by the motion planner. The trajectory tracking controllers based on PID control method were able to track the reference trajectory with good performances. The trade-off between motion sickness and journey time was solved using the application of multi-objective optimisation by altering the weighting factors to find a compromise solution. The Pareto front representing the correlation between the two components is obtained and this front also allows user to select their preference driving style. From the three case studies, driving styles have a bigger impact on reducing motion sickness and journey time rather than vehicle speed and the road width. However, the effect of road width is negligible when travelling on longer road for the reduction of motion sickness and journey time. This finding is crucial considering the need for automated vehicles to drive on a fixed road path in respect to road safety and also to allow the employment of connected and automated vehicles in the future. Finally, an approach combining two optimisation algorithms, the optimal control problem and the k - є method, is applied successfully to seek the best trajectory profile that ensures the optimum compromise between motion comfort and driving behaviour, energy efficiency, vehicle stability, occupant's confidence to ride and journey time.Item Open Access Controllability, observability in networked control(Elsevier, 2009-06-18) Longo, Stefano; Herrmann, Guido; Barber, PhilWe reconsider and advance the analysis of structural properties (controllability and observability) of a class of linear Networked Control Systems (NCSs). We model the NCS as a periodic system with limited communication where the non updated signals can either be held constant (the zero-order-hold case) or reset to zero. Periodicity is dealt using the lifting technique. We prove that a communication sequence that avoids particularly defined pathological sampling rates and updates each actuator signal only once is sufficient to preserve controllability (and observability for the dual problem of sensor scheduling). These sequences can be shorter than previously established and we set a tight lower bound to them.Item Open Access Cost functions for degradation control of electric motors in electric vehicles(Institute of Electrical and Electronics Engineers, 2015-11-16) Samaranayake, Lilantha; Longo, StefanoThis paper introduces a novel set of electric motor degradation cost functions based on energy usage, energy loss and work output, against their continuous operation rated values recommended by the manufacturer. Unlike conventional electric motor degradation indicators such as the bearing life and insulation life based service factors, these cost functions account for the quantified time in the degradation process. The cost functions are evaluated throughout the operational life of the motor using real-time measurements. Hence, they give a very accurate indication, which may be adapted for online controller tuning. This solid establishment of a degradation cost function also enables the system designer to give the user a choice between performance and degradation minimization. The proposed cost function scheme has experimentally been verified using a hardware-in-the-loop electric powertrain test-rig where standard drive cycles are used to conduct the experiments. The experimental results reveal that the degradation cost functions Cumulative Input Energy Ratio (CIER), Cumulative Loss Ratio (CLR) and Cumulative Work Ratio (CWR) accurately represent the electric motor degradation both qualitatively and quantitatively.Item Open Access Data for "Electric Vehicle Battery Parameter Identification and SOC Observability Analysis: NiMH and Li-S Case Studies"(Cranfield University, 2017-11-21 11:49) Fotouhi, Abbas; Auger, Daniel; Propp, Karsten; Longo, StefanoIn this study, battery model identification is performed to be applied in electric vehicle battery management systems. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and lithium-sulfur (Li-S), a promising next-generation technology. Equivalent circuit battery model parameterization is performed in both cases using the Prediction-Error Minimization (PEM) algorithm applied to experimental data. Performance of a Li-S cell is also tested based on urban dynamometer driving schedule (UDDS) and the proposed parameter identification framework is applied in this case as well. The identification results are then validated against the exact values of the battery parameters. The use of identified parameters for battery state-of-charge (SOC) estimation is also discussed. It is shown that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereas Li-S battery SOC estimation is more challenging due to its unique features such as flat OCV-SOC curve. An observability analysis shows that Li-S battery SOC is not fully observable and the existing methods in the literature might not be applicable for a Li-S cell. Finally, the effect of temperature on the identification results and the observability are discussed by repeating the UDDS test at 5, 10, 20, 30, 40 and 50 degree Celsius. File created in MATLAB 2015a.Item Open Access Data for "Lithium-Sulfur Battery State-of-Charge Observability Analysis and Estimation"(Cranfield University, 2017-11-21 11:49) Fotouhi, Abbas; Auger, Daniel; Propp, Karsten; Longo, Stefano3.4 Ah Li-S cell pulse discharge test data at 30 degree. File created in MATLAB 2015a.Item Open Access Degradation control for electric vehicle machines using nonlinear model predictive control(IEEE, 2017-01-17) Samaranayake, Lilantha; Longo, StefanoElectric machines (motors and generators) are over actuated systems. In this paper, we show how to exploit this actuation redundancy in order to mitigate machine degradation while simultaneously ensuring that the desired closed loop performance is maintained. We formulate a multiobjective optimization problem with a cost function having terms representing closed loop performance and component degradation for an inverter-fed permanent magnet synchronous motor. Such machines are important as they are widely used as the prime mover of commercial electric vehicles. The resulting optimal control problem is implemented online via a nonlinear model predictive control (NMPC) scheme. The control framework is validated for standard vehicle drive cycles. Results show that the NMPC scheme allows for better closed loop performance and lower degradation than standard industrial controllers, such as the field-oriented control method. Hence, this paper demonstrates how the remaining useful life of a machine can be increased by appropriate controller design without compromising performance.Item Open Access Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies(The Institution of Engineering and Technology, 2017-07-06) Fotouhi, Abbas; Auger, Daniel J.; Propp, Karsten; Longo, StefanoIn this study, battery model identification is performed to be applied in electric vehicle battery management systems. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and lithium-sulphur (Li-S), a promising next-generation technology. Equivalent circuit battery model parameterisation is performed in both cases using the prediction-error minimisation algorithm applied to experimental data. Performance of a Li-S cell is also tested based on urban dynamometer driving schedule (UDDS) and the proposed parameter identification framework is applied in this case as well. The identification results are then validated against the exact values of the battery parameters. The use of identified parameters for battery state-of-charge (SOC) estimation is also discussed. It is shown that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereas Li-S battery SOC estimation is more challenging due to its unique features such as flat OCV–SOC curve. An observability analysis shows that Li-S battery SOC is not fully observable and the existing methods in the literature might not be applicable for a Li-S cell. Finally, the effect of temperature on the identification results and the observability is discussed by repeating the UDDS test at 5, 10, 20, 30, 40 and 50°C.Item Open Access Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies(IET, 2016-04-21) Fotouhi, Abbas; Auger, Daniel J.; Propp, Karsten; Longo, StefanoIn this study, a framework is proposed for battery model identification to be applied in electric vehicle energy storage systems. The main advantage of the proposed approach is having capability to handle different battery chemistries. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and Lithium-Sulphur (Li-S), a promising next-generation technology. Equivalent circuit battery model parametrisation is performed in both cases using the Prediction-Error Minimization (PEM) algorithm applied to experimental data. The use of identified parameters for battery state-of-charge (SOC) estimation is then discussed. It is demonstrated that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery’s open circuit voltage (OCV) is adequate for SOC estimation. However, Li-S battery SOC estimation can be challenging due to the chemistry’s unique features and the SOC cannot be estimated from the OCV-SOC curve alone because of its flat gradient. An observability analysis demonstrates that Li-S battery SOC is not observable using the common state-space representations in the literature. Finally, the problem’s solution is discussed using the proposed framework.Item Open Access Energy-aware MPC co-design for DC-DC converters(Institute of Electrical and Electronics Engineers, 2013-07-22) Suardi, Andrea; Longo, Stefano; Kerrigan, Eric C.; Constantinides, George A.In this paper, we propose an integrated controller design methodology for the implementation of an energy-aware explicit model predictive control (MPC) algorithms, illustrat- ing the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques, like MPC, are used. For DC-DC converters, digital control provides better regulation, but also higher energy consumption compared to standard analog methods. To overcome the limitation in energy efficiency, instead of addressing the problem by implementing sub-optimal MPC schemes, the closed-loop performance and the control algorithm power consumption are minimized in a joint cost function, allowing us to keep the controller power efficiency closer to an analog approach while maintaining closed-loop op- timality. A case study for an implementation in reconfigurable hardware shows how a designer can optimally trade closed-loop performance with hardware implementation performance.Item Open Access ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants(Elsevier, 2019-03-21) Longo, Stefano; Mauricio-Iglesias, Miguel; Soares, Ana; Campo Moreno, Pablo; Fatone, Francesco; Eusebi, Anna L.; Akkersdijk, E; Stefani, L.; Hospido, AlmudenaThis paper describes the first methodology specifically tailored to estimate energy efficiency at wastewater treatment plants (WWTPs). Inspired by the cycle of continuous improvement, the method (i) precisely defines the concept of energy efficiency in WWTPs, (ii) proposes systematic and comparable ways to measure it, and (iii) allows benchmarking and diagnosing energy hotspots. The methodology delivers an aggregated measure of the WWTP energy efficiency defined as the Water Treatment Energy Index, a single energy label that uses universally known illustrations enabling wide communication of standardized information on the WWTP energy status. The accuracy, reproducibility and generality of the methodology were validated by a widespread energy benchmarking method, and a case study is presented to show its capabilities. By promoting dialogue towards the creation of a specific European Standard, the actions accomplished by the H2020 Coordination Support Action ENERWATER should positively contribute to improving the exchange of information on energy saving actions and results between wastewater utilities and towards other stakeholders.Item Open Access Feedback brake distribution control for minimum pitch(Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017-03-03) Tavernini, Davide; Velenis, Efstathios; Longo, StefanoThe distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as ‘ideal’ distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference ‘ideal’ distribution as well as another previous feed-forward solution.Item Open Access A framework for self-enforced optimal interaction between connected vehicles(IEEE, 2020-05-06) Stryszowski, Marcin; Longo, Stefano; D'Alessandro, Dario; Velenis, Efstathios; Forostovsky, Gregory; Manfredi, SabatoThis paper proposes a decision-making framework for Connected Autonomous Vehicle interactions. It provides and justifies algorithms for strategic selection of control references for cruising, platooning and overtaking. The algorithm is based on the trade-off between energy consumption and time. The consequent cooperation opportunities originating from agent heterogeneity are captured by a game-theoretic cooperative-competitive solution concept to provide a computationally feasible, self-enforced, cooperative traffic management framework.Item Open Access Fundamentals of motion planning for mitigating motion sickness in automated vehicles(IEEE, 2021-12-28) Htike, Zaw; Papaioannou, Georgios; Siampis, Efstathios; Velenis, Efstathios; Longo, StefanoThis paper investigates the fundamentals of motion planning for minimizing motion sickness in transportation systems of higher automation levels. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimize the motion sickness and the journey time. An empirical approach based on British standard is used to evaluatemotion sickness. The tradeo between minimizing motion sickness and journey time is investigated through multi-objective optimization by altering the weighting factors. The correlation between sickness and journey time is represented as a Pareto front because of their conflicting relation. The compromise between the two components is quantified along the curve, while the severity of the sickness is determined using frequency analysis. In addition, three case studies are developed to investigate the eect of driving style, vehicle speed, and road width, which can be considered among the main factors aecting motion sickness. According to the results, the driving style has higher impact on both motion sickness and journey time compared to the vehicle speed and the road width. The benefit of higher vehicle speed gives shorter journey time while maintaining relatively lower illness rating compared with lower vehicle speed. The eect of the road width is negligible on both sickness and journey time when travelling on a longer road.The results pave the path for the development of vehicular technologies to implement for real-world driving from the outcomes of this paper.Item Open Access Fuzzy logic control for energy saving in autonomous electric vehicles(IEEE, 2015-03-06) Al-Jazaeri, Ahmed O.; Samaranayake, Lilantha; Longo, Stefano; Auger, Daniel J.Limited battery capacity and excessive battery dimensions have been two major limiting factors in the rapid advancement of electric vehicles. An alternative to increasing battery capacities is to use better: intelligent control techniques which save energy on-board while preserving the performance that will extend the range with the same or even smaller battery capacity and dimensions. In this paper, we present a Type-2 Fuzzy Logic Controller (Type-2 FLC) as the speed controller, acting as the Driver Model Controller (DMC) in Autonomous Electric Vehicles (AEV). The DMC is implemented using realtime control hardware and tested on a scaled down version of a back to back connected brushless DC motor setup where the actual vehicle dynamics are modelled with a Hardware-In-the-Loop (HIL) system. Using the minimization of the Integral Absolute Error (IAE) has been the control design criteria and the performance is compared against Type-1 Fuzzy Logic and Proportional Integral Derivative DMCs. Particle swarm optimization is used in the control design. Comparisons on energy consumption and maximum power demand have been carried out using HIL system for NEDC and ARTEMIS drive cycles. Experimental results show that Type-2 FLC saves energy by a substantial amount while simultaneously achieving the best IAE of the control strategies tested.Item Open Access A hardware-in-the-loop test rig for development of electric vehicle battery identification and state estimation algorithms(Inderscience, 2018-03-01) Fotouhi, Abbas; Propp, Karsten; Samaranayake, Lilantha; Auger, Daniel J.; Longo, StefanoThis paper describes a hardware-in-the-loop (HIL) test rig for the test and development of electric vehicle battery parameterisation and state-estimation algorithms in the presence of realistic real-world duty cycles. The rig includes two electric machines, a battery pack, a real-time simulator, a thermal chamber and a PC for human-machine interface. Other parts of a vehicle powertrain system are modelled and used in the real-time simulator. A generic framework has been developed for real-time battery measurement, model identification and state estimation. Measurements are used to extract parameters of an equivalent circuit network model. Outputs of the identification unit are then used by an estimation unit trained to find the relationship between the battery parameters and state-of-charge. The results demonstrate that even with a high noise level in measured data, the proposed identification and estimation algorithms are able to work well in real-time.