The novel application of optimization and charge blended energy management control for component downsizing within a plug-in hybrid electric vehicle

The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialization. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Contained within this paper is an optimization study in which a charge blended strategy is used to facilitate the downsizing of the electrical machine, the internal combustion engine and the high voltage battery. An improved Equivalent Consumption Method has been used to manage the optimal power split within the powertrain as the PHEV traverses a range of different drivecycles. For a target CO2 value and drivecycle, results show that this approach can yield significant downsizing opportunities, with cost reductions on the order of 2%–9% being realizable

Optimal battery charge/discharge strategies for prosumers and suppliers

We discuss the application of classical variational methods to optimal charging/discharging strategies for a prosumer or storage supplier, where the price of electrical power is known in advance. We outline how a classical calculus of variations approach can be applied to two related problems: (i) how can a prosumer minimise the cost of charging/discharging a battery, when the price of electrical power is known throughout the charging/discharging period? and (ii) how can an electricity supplier incentivise desired prosumer/storage supplier behaviour by adjusting the price

Investigation of ventricular cerebrospinal fluid flow phase differences between the foramina of Monro and the aqueduct of Sylvius

In this paper, phase contrast magnetic resonance flow measurements of the foramina of Monro and the aqueduct of Sylvius of seven healthy volunteers are presented. Peak volume flow rates are of the order of 150 mm3/s for the aqueduct of Sylvius and for the foramina of Monro. The temporal shift between these volume flows is analyzed with a high-resolution cross-correlation scheme which reveals high subject-specific phase differences. Repeated measurements show the invariability of the phase differences over time for each volunteer. The phase differences as a fraction of one period range from -0.0537 to 0.0820. A mathematical model of the pressure dynamics is presented. The model features one lumped compartment per ventricle. The driving force of the cerebrospinal fluid is modeled through pulsating choroid plexus. The model includes variations of the distribution of the choroid plexus between the ventricles. The proposed model is able to reproduce the measured phase differences with a very small (5%) variation of the distribution of the choroid plexus between the ventricles and, therefore, supports the theory that the choroid plexus drives the cerebrospinal fluid motio

Evolutionary Optimization of Feedback Controllers for Thermoacoustic Instabilities

International audienceWe present the system identifcation and the online optimization of feedback controllers applied to combustion systems using evolutionary algorithms. The algorithm is applied to gas turbine combustors that are susceptible to thermoacoustic instabilities resulting in imperfect combustion and decreased lifetime. In order to mitigate these pressure oscillations, feedback controllers sense the pressure and command secondary fuel injectors. The controllers are optimized online with an extension of the CMA evolution strategy capable of handling noise associated with the uncertainties in the pressure measurements. The presented method is independent of the specifc noise distribution and prevents premature convergence of the evolution strategy. The proposed algorithm needs only two additional function evaluations per generation and is therefore particularly suitable for online optimization. The algorithm is experimentally verifed on a gas turbine combustor test rig. The results show that the algorithm can improve the performance of controllers online and is able to cope with a variety of time dependent operating conditions

Variable-structure control with complementarity-inputs for a lean-burn IC engine of a series hybrid vehicle

This paper presents a robust controller for an internal combustion (IC) engine, as the first stage of a project to develop a hybrid light urban vehicle, running on ethanol in lean burn. In particular, this work focuses on the design of a sliding mode control for an IC engine of a series hybrid power train. The controller must allow for optimal speed regulation and high fuel efficiency. To attain the latter, a complementary operation mode is proposed for the system inputs. Simulation results are presented and discussed showing the viability and advantages of the control strategy employed.Postprint (author's final draft

Deltoid, triceps, or both responses improve the success rate of the interscalene catheter surgical block compared with the biceps response

Background The influence of the muscular response elicited by neurostimulation on the success rate of interscalene block using a catheter (ISC) is unknown. In this investigation, we compared the success rate of ISC placement as indicated by biceps or deltoid, triceps, or both twitches. Methods Three hundred (ASA I-II) patients presenting for elective arthroscopic rotator cuff repair were prospectively randomized to assessment by biceps (Group B) or deltoid, triceps, or both twitches (Group DT). All ISCs were placed with the aid of neurostimulation. The tip of the stimulating needle was placed after disappearance of either biceps or deltoid, triceps, or both twitches at 0.3 mA. The catheter was advanced 2-3 cm past the tip of the needle and the block was performed using 40 ml ropivacaine 0.5%. Successful block was defined as sensory block of the supraclavicular nerve and sensory and motor block involving the axillary, radial, median, and musculocutaneous nerves within 30 min. Results Success rate was 98.6% in Group DT compared with 92.5% in Group B (95% confidence interval 0.01-0.11; P<0.02). Supplemental analgesics during handling of the posterior part of the shoulder capsule were needed in two patients in Group DT and seven patients in Group B. Three patients in Group B had an incomplete radial nerve distribution anaesthesia necessitating general anaesthesia. One patient in Group B had an incomplete posterior block extension of the supraclavicular nerve. No acute or late complications were observed. Conclusions Eliciting deltoid, triceps, or both twitches was associated with a higher success rate compared with eliciting biceps twitches during continuous interscalene bloc

Modelling driving behaviour and its impact on the energy management problem in hybrid electric vehicles

Perfect knowledge of future driving conditions can be rarely assumed on real applications when optimally splitting power demands among different energy sources in a hybrid electric vehicle. Since performance of a control strategy in terms of fuel economy and pollutant emissions is strongly affected by vehicle power requirements, accurate predictions of future driving conditions are needed. This paper proposes different methods to model driving patterns with a stochastic approach. All the addressed methods are based on the statistical analysis of previous driving patterns to predict future driving conditions, some of them employing standard vehicle sensors, while others require non-conventional sensors (for instance, global positioning system or inertial reference system). The different modelling techniques to estimate future driving conditions are evaluated with real driving data and optimal control methods, trading off model complexity with performance.Guardiola García, C.; Plá Moreno, B.; Blanco Rodriguez, D.; Reig Bernad, A. (2014). Modelling driving behaviour and its impact on the energy management problem in hybrid electric vehicles. International Journal of Computer Mathematics. 91(1):147-156. doi:10.1080/00207160.2013.829567S147156911Ericsson, E. (2001). Independent driving pattern factors and their influence on fuel-use and exhaust emission factors. Transportation Research Part D: Transport and Environment, 6(5), 325-345. doi:10.1016/s1361-9209(01)00003-7Q. Gong, P. Tulpule, V. Marano, S. Midlam-Mohler, and G. Rizzoni,The role of ITS in PHEV performance improvement, 2011 American Control Conference, June–July, San Francisco, CA, 2011, pp. 2119–2124.C. Guardiola, B. Pla, S. Onori, and G. Rizzoni,A new approach to optimally tune the control strategy for hybrid vehicles applications, IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM’12, October, Rueil-Malmaison, France, 2012.Johannesson, L., Asbogard, M., & Egardt, B. (2007). Assessing the Potential of Predictive Control for Hybrid Vehicle Powertrains Using Stochastic Dynamic Programming. IEEE Transactions on Intelligent Transportation Systems, 8(1), 71-83. doi:10.1109/tits.2006.884887Liu, S., & Yao, B. (2008). Coordinate Control of Energy Saving Programmable Valves. IEEE Transactions on Control Systems Technology, 16(1), 34-45. doi:10.1109/tcst.2007.903073Paganelli, G. (2001). General supervisory control policy for the energy optimization of charge-sustaining hybrid electric vehicles. JSAE Review, 22(4), 511-518. doi:10.1016/s0389-4304(01)00138-2Rizzoni, G., Guzzella, L., & Baumann, B. M. (1999). Unified modeling of hybrid electric vehicle drivetrains. IEEE/ASME Transactions on Mechatronics, 4(3), 246-257. doi:10.1109/3516.789683Control of hybrid electric vehicles. (2007). IEEE Control Systems, 27(2), 60-70. doi:10.1109/mcs.2007.338280L. Serrao, S. Onori, and G. Rizzoni,ECMS as realization of Pontryagin's minimum principle for HEV control, 2009 American Control Conference, June, Saint Louis, MO, 2009, pp. 3964–3969.Serrao, L., Onori, S., & Rizzoni, G. (2011). A Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles. Journal of Dynamic Systems, Measurement, and Control, 133(3). doi:10.1115/1.4003267Stockar, S., Marano, V., Canova, M., Rizzoni, G., & Guzzella, L. (2011). Energy-Optimal Control of Plug-in Hybrid Electric Vehicles for Real-World Driving Cycles. IEEE Transactions on Vehicular Technology, 60(7), 2949-2962. doi:10.1109/tvt.2011.2158565Sundström, O., Ambühl, D., & Guzzella, L. (2009). On Implementation of Dynamic Programming for Optimal Control Problems with Final State Constraints. Oil & Gas Science and Technology – Revue de l’Institut Français du Pétrole, 65(1), 91-102. doi:10.2516/ogst/2009020O. Sundström and L. Guzzella,A generic dynamic programming Matlab function, 18th IEEE International Conference on Control Applications Part of 2009 IEEE Multi-conference on Systems and Control, July, Saint Petersburg, 2009, pp. 1625–1630.R. Wang and S.M. Lukic,Review of driving conditions prediction and driving style recognition based control algorithms for hybrid electric vehicles, Vehicle Power and Propulsion Conference (VPPC), 2011 IEEE, September 6–9, Raleigh, NC, 2011, pp. 1–7