DDAH1 and nNOS expression in the ventral tegmental area in relation to dopamine neurons

Nitric oxide (NO) is an important signalling molecule. One-way that NO’s production is regulated is through the asymmetric dimethylarginine (ADMA)-dimethylarginine-dimethylaminohydrolase (DDAH) pathway. One role of NO in the brain is as a negative feedback signal in ventral tegmental area (VTA) dopamine (DA) neurons. It has been shown through electrophysiology that in response to depolarisation NO diffuses retrogradely and potentiates GABA release, which in turn inhibits DA neuron activity. It has been hypothesised on the basis of electrophysiology and pharmacology experiments that NO is produced by VTA DA neurons. However although both DDAH1 and nitric oxide synthase (nNOS; which is the source of neuronal NO) are expressed in the VTA, it is not clear in which cell types. I, therefore, used immunohistochemistry to investigate nNOS and DDAH1 expression in the parabrachial pigmented area (PBP) of the VTA. The PBP is where most electrophysiological recordings from DA neurons in the VTA are carried out. I found that nNOS is expressed in the PBP of the VTA in close proximity to, but not colocalized, with DA neuron cell bodies and processes. This may indicate that NO production occurs in another cell type in response to VTA stimulation. Although DDAH1 expression was found in both DA and non-DA cells in the PBP, staining was present, although noticeably weaker, in DDAH1 global knockout mice. Thus no firm conclusion can be drawn on DDAH1 expression in the VTA.Open Acces

Generating realistic data for developing artificial neural network based SOC estimators for electric vehicles

Tracking the state of a lithium-ion battery in an electric vehicle (EV) is a challenging task. In order to tackle one aspect of this task, we choose a data-driven approach for estimating the State of Charge (SOC), which is one of the most import parameters. In this context, the quality of the provided data is of utmost importance. Usually, standardized driving profiles are used to generate current profiles which are then applied to battery cells during testing. However, these standardized driving profiles exhibit significant deviation from real-world conditions, which can considerably affect the learning and validation performance of data-driven approaches. In this paper, we first propose a test profile generator which generates realistic current profiles for EV battery testing. Second, to demonstrate the effect of the proposed test profiles a multilayer perceptron (MLP) based SOC estimator is presented. Finally, we compare the results to the standardized driving profiles

Hardware-in-the-Loop Test Rig for Rapid Prototyping of Battery Management System Algorithms

Testing the performance of a battery management system (BMS) is extensive and crucial due to its importance for the overall battery safety and performance. In this paper, a hardware-in-the-loop (HiL) test bench is presented for rapid prototyping, testing and evaluation of BMS algorithms in realtime. The system is designed to work with real cell packs without any additional electronics or casing. This approach avoids the high cost and effort of building a full battery system and therefore simplifies algorithm testing on different cell types and cell pack topologies. An extended Kalman Filter based state-of-charge-algorithm is developed and compiled in C-Code in MATLAB/Simulink to run on a digital signal processor (DSP) in real-time. The capabilities and advantages of the setup are shown with experimental HiL tests of the developed BMS algorithm in comparison to software-in-the-loop (SiL) tests

Generating realistic data for developing artificial neural network based SOC estimators for electric vehicles

Tracking the state of a lithium-ion battery in an electric vehicle (EV) is a challenging task. In order to tackle one aspect of this task, we choose a data-driven approach for estimating the State of Charge (SOC), which is one of the most import parameters. In this context, the quality of the provided data is of utmost importance. Usually, standardized driving profiles are used to generate current profiles which are then applied to battery cells during testing. However, these standardized driving profiles exhibit significant deviation from real-world conditions, which can considerably affect the learning and validation performance of data-driven approaches. In this paper, we first propose a test profile generator which generates realistic current profiles for EV battery testing. Second, to demonstrate the effect of the proposed test profiles a multilayer perceptron (MLP) based SOC estimator is presented. Finally, we compare the results to the standardized driving profiles

Hardware-in-the-Loop Test Rig for Rapid Prototyping of Battery Management System Algorithms

Testing the performance of a battery management system (BMS) is extensive and crucial due to its importance for the overall battery safety and performance. In this paper, a hardware-in-the-loop (HiL) test bench is presented for rapid prototyping, testing and evaluation of BMS algorithms in real-time. The system is designed to work with real cell packs without any additional electronics or casing. This approach avoids the high cost and effort of building a full battery system and therefore simplifies algorithm testing on different cell types and cell pack topologies. An extended Kalman Filter based state-of-charge-algorithm is developed and compiled in C-Code in MATLAB/Simulink to run on a digital signal processor (DSP) in real-time. The capabilities and advantages of the setup are shown with experimental HiL tests of the developed BMS algorithm in comparison to software-in-the-loop (SiL) tests

Effects of Realistic Driving Profiles on the Degradation of Lithium-Ion Batteries

In dieser Studie werden die Alterungseigenschaften von Lithium-Ionen-Batterien unter konventionellen Zyklustests und realistischen Fahrprofilprüfungen untersucht. Wir verwenden regelmäßige Kapazitätstests und elektrochemische Impedanzspektroskopie für eine umfassende Analyse des Gesundheitszustandes. Für diese Untersuchung haben wir handelsübliche, runde LFP-Zellen im Format 21700 verwendet. Die Ergebnisse zeigen einen stärkeren Kapazitätsverlust bei realistischen Fahrprofilen im Vergleich zu konventionellen Zyklen. Diese Diskrepanz deutet darauf hin, dass die Rekuperationsphasen ein Schlüsselfaktor für die beschleunigte Alterung von Lithium-Ionen-Batterien sind, die in Elektrofahrzeugen eingesetzt werden. Diese Forschung unterstreicht die Bedeutung realistischer Belastungsszenarien für die Bewertung der Batterielebensdauer und kann zur Entwicklung fortschrittlicherer Batteriemanagementsysteme in Elektrofahrzeugen beitragen

Hardware-in-the-Loop Setup for a Modular Multilevel Converter with Integrated Batteries

A hardware-in-the-loop setup to emulate a modular multilevel converter (MMC) with batteries integrated in its submodules is presented. It allows the testing of control methods without a real converter. A state-space MMC model is introduced, extended by RC battery models and implemented on an FPGA. The scalability of battery models for converters with large numbers of submodules is shown. The emulation closes the loop for a combined MMC-controller and battery management algorithm under test, running on an ARM processor. Given the modular approach, the level of detail for power electronics, batteries and control schemes can be adapted independently

Hardware-in-the-Loop Setup for a Modular Multilevel Converter with Integrated Batteries

A hardware-in-the-loop setup to emulate a modular multilevel converter (MMC) with batteries integrated in its submodules is presented. It allows the testing of control methods without a real converter. A state-space MMC model is introduced, extended by RC battery models and implemented on an FPGA. The scalability of battery models for converters with large numbers of submodules is shown. The emulation closes the loop for a combined MMC-controller and battery management algorithm under test, running on an ARM processor. Given the modular approach, the level of detail for power electronics, batteries and control schemes can be adapted independently