A scalable life cycle inventory of an electrical automotive traction machine—part I: design and composition

Purpose: A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models’ mass estimations. Methods: Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines’ maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20–200 kW and 48–477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands. Results and discussion: The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models’ mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96–97%. Conclusions: The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking

Thermal capability of electric vehicle PMSM with different slot areas via thermal network analysis

In this paper, the effect that a varied stator slot size has on the efficiency and thermal capability of a permanent magnet synchronous machine for an electric vehicle, is evaluated and quantified. A machine with four differently sized slot areas was electromagnetically evaluated with finite element analysis, and thermally with a lumped parameter network model. By decreasing the slot size while keeping other dimensions fixed, the core losses reduce due to the wider magnetic path, whereas the winding losses increase. Additionally, a higher maximum torque is reached due to reduced saturation. Results are compared in the machine\u27s torque-speed operating area regarding machine-part and total losses, continuous torque and transient overload capability, as well as during 19 low, middle and high-speed drive cycles regarding energy losses and peak winding temperature. The largest slot showed the lowest winding losses and thus the highest thermally limited torque capability. In contrast, the energy losses with the largest slot were the highest in 13 of the drive cycles, and the lowest in 11 of them with the smallest slot due to its lower part load (i.e. core) losses. The smallest slot would also result in the lowest material cost since it has the least copper

A scalable life cycle inventory of an electrical automotive traction machine—part I: design and composition

Purpose: A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models’ mass estimations. Methods: Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines’ maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20–200 kW and 48–477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands. Results and discussion: The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models’ mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96–97%. Conclusions: The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking

Spine neck plasticity regulates compartmentalization of synapses

Dendritic spines have been proposed to transform synaptic signals through chemical and electrical compartmentalization. However, the quantitative contribution of spine morphology to synapse compartmentalization and its dynamic regulation are still poorly understood. We used time-lapse super-resolution stimulated emission depletion (STED) imaging in combination with fluorescence recovery after photobleaching (FRAP) measurements, two-photon glutamate uncaging, electrophysiology and simulations to investigate the dynamic link between nanoscale anatomy and compartmentalization in live spines of CA1 neurons in mouse brain slices. We report a diversity of spine morphologies that argues against common categorization schemes and establish a close link between compartmentalization and spine morphology, wherein spine neck width is the most critical morphological parameter. We demonstrate that spine necks are plastic structures that become wider and shorter after long-term potentiation. These morphological changes are predicted to lead to a substantial drop in spine head excitatory postsynaptic potential (EPSP) while preserving overall biochemical compartmentalization

Biphasic Synaptic Ca Influx Arising from Compartmentalized Electrical Signals in Dendritic Spines

Dendritic spines compartmentalize synaptically-evoked biochemical signals. The authors show that electrical compartmentalization provided by a spine endows the associated synapse with additional modes of calcium signaling by shaping the kinetics of synaptic calcium currents

Subcellular Location of PKA Controls Striatal Plasticity: Stochastic Simulations in Spiny Dendrites

Dopamine release in the striatum has been implicated in various forms of reward dependent learning. Dopamine leads to production of cAMP and activation of protein kinase A (PKA), which are involved in striatal synaptic plasticity and learning. PKA and its protein targets are not diffusely located throughout the neuron, but are confined to various subcellular compartments by anchoring molecules such as A-Kinase Anchoring Proteins (AKAPs). Experiments have shown that blocking the interaction of PKA with AKAPs disrupts its subcellular location and prevents LTP in the hippocampus and striatum; however, these experiments have not revealed whether the critical function of anchoring is to locate PKA near the cAMP that activates it or near its targets, such as AMPA receptors located in the post-synaptic density. We have developed a large scale stochastic reaction-diffusion model of signaling pathways in a medium spiny projection neuron dendrite with spines, based on published biochemical measurements, to investigate this question and to evaluate whether dopamine signaling exhibits spatial specificity post-synaptically. The model was stimulated with dopamine pulses mimicking those recorded in response to reward. Simulations show that PKA colocalization with adenylate cyclase, either in the spine head or in the dendrite, leads to greater phosphorylation of DARPP-32 Thr34 and AMPA receptor GluA1 Ser845 than when PKA is anchored away from adenylate cyclase. Simulations further demonstrate that though cAMP exhibits a strong spatial gradient, diffusible DARPP-32 facilitates the spread of PKA activity, suggesting that additional inactivation mechanisms are required to produce spatial specificity of PKA activity

Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

The rapidly increasing penetration of electric vehicles in modern metropolises has been witnessed during the past decade, inspired by financial subsidies as well as public awareness of climate change and environment protection. Integrating charging facilities, especially high-power chargers in fast charging stations, into power distribution systems remarkably alters the traditional load flow pattern, and thus imposes great challenges on the operation of distribution network in which controllable resources are rare. On the other hand, provided with appropriate incentives, the energy storage capability of electric vehicle offers a unique opportunity to facilitate the integration of distributed wind and solar power generation into power distribution system. The above trends call for thorough investigation and research on the interdependence between transportation system and power distribution system. This paper conducts a comprehensive survey on this line of research. The basic models of transportation system and power distribution system are introduced, especially the user equilibrium model, which describes the vehicular flow on each road segment and is not familiar to the readers in power system community. The modelling of interdependence across the two systems is highlighted. Taking into account such interdependence, applications ranging from long-term planning to short-term operation are reviewed with emphasis on comparing the description of traffic-power interdependence. Finally, an outlook of prospective directions and key technologies in future research is summarized.fi=vertaisarvioitu|en=peerReviewed

Drive Cycle Evaluation and Consumption of PM Motors for a Typical Battery Electric City Bus

Four permanent magnet electric machines for a typical battery electric city bus (BECB) are compared regarding drive cycle energy consumption during 18 official and one logged bus drive cycle. Two machine types are used; an interior permanent magnet synchronous machine (IPMSM) with a two layer distributed winding (DW), and an IPMSM with tooth coil windings (TCW), both with either copper or aluminum winding material. The results are aimed for a life cycle assessment study of electric machines in a typical BECB. A conducted BECB market survey is shortly summarized, and 40 official bus drive cycles are characterized using the chosen bus dimensions