On M2M Micropayments : A Case Study of Electric Autonomous Vehicles

The proliferation of electric vehicles has spurred the research interest in technologies associated with it, for instance, batteries, and charging mechanisms. Moreover, the recent advancements in autonomous cars also encourage the enabling technologies to integrate and provide holistic applications. To this end, one key requirement for electric vehicles is to have an efficient, secure, and scalable infrastructure and framework for charging, billing, and auditing. However, the current manual charging systems for EVs may not be applicable to the autonomous cars that demand new, automatic, secure, efficient, and scalable billing and auditing mechanism. Owing to the distributed systems such as blockchain technology, in this paper, we propose a new charging and billing mechanism for electric vehicles that charge their batteries in a charging-on-the-move fashion. To meet the requirements of billing in electric vehicles, we leverage distributed ledger technology (DLT), a distributed peer-to-peer technology for micro-transactions. Our proof-of-concept implementation of the billing framework demonstrates the feasibility of such system in electric vehicles. It is also worth noting that the solution can easily be extended to the electric autonomous cars (EACs)

An architecture for distributed ledger-based M2M auditing for Electric Autonomous Vehicles

Electric Autonomous Vehicles (EAVs) promise to be an effective way to solve transportation issues such as accidents, emissions and congestion, and aim at establishing the foundation of Machine-to-Machine (M2M) economy. For this to be possible, the market should be able to offer appropriate charging services without involving humans. The state-of-the-art mechanisms of charging and billing do not meet this requirement, and often impose service fees for value transactions that may also endanger users and their location privacy. This paper aims at filling this gap and envisions a new charging architecture and a billing framework for EAV which would enable M2M transactions via the use of Distributed Ledger Technology (DLT)

Improvement of Li-ion Battery Active Balancer Using PI-Controller

This paper presents simulation and design for the improvement of Li-ion battery ac-tive balancer using PI controller. The growing market for lithium ion (Li-ion) battery cells has made a positive impact towards electrical energy storage (EES) system throughout the advancing technological and scientific world. Balancing in a battery pack has become a main priority to avoid over-charging and over-discharging while also improving the Li-ion battery life. Unlike passive balancing, active balancing transfers the energy from one cell to another or controls the cell’s output, thus im-proving its efficiency. This paper presents how previous work was accomplished by many scholars in order to avail themselves of the active balancing project. A cell model was shown in this paper that was built based on energy transfer circuit theo-ries. A capacitor(C), inductor (L), MOSFET (M) and Diode (D) were used in the circuit build in order to balance the cells of different State-of-Charge (SOC). A PI controller was added with circuit to improve the voltage efficiency. After adding PI controller, the voltage balance of the cell was seen improved

A Technical Review of BMS Performance Standard for Electric Vehicle Applications in Indonesia

The development of Battery Management System (BMS) standards in Indonesia has been carried out causing the FACTS approach. That's approach makes it possible to accommodate all stakeholder requirements. However, the approach has not yet considered a technical review of the regulated standards. Based on this, this study undertook a comprehensive review of BMS performance parameters set out in the standard. In order that the regulated standards not only accommodate the needs of stakeholders but also consider BMS technical studies in order not to impede the future development of BMS

Energy storage impact on light rail developments

– Smart cities imply a range of efficient mobility solutions for people and goods at the same time as minimising the environmental burden. This short paper focuses on Light Rail and particularly Tram systems as having advantages in responding to these needs and is the first stage on a longer project which will provide greater detail in due course. It further considers the alternatives for powering the system as an important component in the development of a clean, attractive and economic urban mass transit resource for the smart city. This leads to energy storage as a potential alternative to continuous energy supply such as overhead cables, and is followed by a comparison of various methods of on-board energy storage including batteries, supercapacitors and hydrogen. Interim conclusions are presented

Experimental Analysis of Open-Circuit Voltage Hysteresis in Lithium-Iron-Phosphate Batteries

This paper aims at investigating and modelling the hysteresis in the relationship between state-of-charge and open-circuit voltage of lithium-iron-phosphate batteries. A first-order charge relaxation equation was used to describe the hysteresis dynamics. This equation was translated into a voltage-controlled voltage source and included within an equivalent electric circuit of the battery used in online state-of-charge estimators. The effectiveness of the obtained battery model was verified comparing simulated and experimental data

State Of Charge Estimation Of Battery Management System

Battery Management System (BMS) is the essential section which has a fundamental occupation in controlling and getting the electric vehicle. The significant elements of BMS incorporate assessing battery state of charge (SoC) utilizing different calculations and propose highlights towards fostering a smart BMS. Battery checking is indispensable for most electric vehicles (EVs) on the grounds that the security, activity, and, surprisingly, the existence of the traveller relies upon the battery system. This trait is by and large the significant capacity of the battery-management system (BMS to check and control the situation with battery inside their predefined safe working circumstances. The state of charge (SOC) assessment has been executed utilizing Kalman Filter Method, consequently wiping out the restriction of the independent Coulomb counting technique. By displaying the battery with SOC as one of the state factors, SOC can be assessed, which is additionally remedied by the Kalman filtering strategy. The battery boundaries from test results are coordinated in the model, and re-enactment results are approved by try. This examination will apply the Kalman Filter in battery model to appraise the battery SoC in light of reproduction model. Recreation will be done through MATLAB Simulink and the examination will zero in on the blunder and state covariance investigation on the consistency and dependability

Dynamic Modeling and Performance Analysis of Sensible Thermal Energy Storage Systems

In this paper we consider the problem of dynamic performance evaluation for sensible thermal energy storage (TES), with a specific focus on hot water storage tanks. We derive transient performance metrics from second law principles that can be used to guide real-time decision-making aimed toward improving demand response. We show how the transient nature of the metrics can be used not only to influence the values of control variables within the system, but also to mitigate adverse effects of disturbances during operation. To evaluate these metrics in the context of TES in hot water storage tanks, a thermal stratification model is needed. We derive a reduced order model which allows the simulation of tank thermal stratification during all modes of system operation. The proposed performance metrics are analyzed in simulation using the dynamic tank model. The results highlight key trade-offs captured by the metrics that can be incorporated into future optimal control design for sensible TES systems. Â

Non-linear kalman filters for battery state of charge estimation and control

In this paper, two different non-linear Kalman Filters for lithium-ion battery state of charge estimation are presented and compared. Nowadays, lithium-ion batteries are extensively used for hybrid and electric vehicles; in such applications, cells are assembled in module and pack to achieve high performance. At this scope, a Battery Management Systems BMS is required to control each cell and improve the battery pack performance, safety, reliability, and lifecycle. One of the major tasks a BMS must fulfill is an accurate online estimation of the State Of Charge (SOC) of the battery pack. In this paper, the Extended Kalman Filter and Sigma Points Kalman filter are developed and compared. A battery equivalent circuit model has been chosen to have a good compromise between complexity and accuracy and model parameters have been identified from Hybrid Pulse Power Characterization (HPPC) tests carried out at different temperatures and current rates to obtain a model valid for a wide range of operating conditions. The SOC estimation strategies are developed starting from the experimental results and it is validated through different driving cycling simulations. The results show that the Sigma Points Kalman filter produces a better estimate of SOC with respect to the Extended Kalman Filter, due to its better capability to deal with system non-linearities, with comparable computational complexity