Impact of Health status of a Battery Electric Vehicle using Cell Balancing Technique

In Present scenario Internal Combustion Engines [ICE] is overcome by Electric Vehicles [EV] due to advantages like reduction in carbon-di-oxide [CO2] emission, cost. Advancement in electric vehicles are extensively going on and one such concept is Battery management system [BMS]in Battery Electric vehicle. In Battery Electric Vehicle there are many types of batteries and from the literature survey Lithium Ion Battery can be concluded to be suitable as it is advantageous in weight, cost, energy density and many aspects. In Battery electric vehicle Battery plays an important role. Battery may be overcharged or it may undergo faults. Hence a proper management system is required to control the Electric vehicle [EV] and it is called Battery Management System [BMS]. In this proposal two battery estimation models are compared and results are tabulated for suitable operation of health status in a Battery Electric Vehicle

Investigating the benefits and limitations of cascaded converter topologies used in modular battery systems

The Performance of battery packs is highly affected by imbalances between the series connected cells that provide the required string voltage. A modular battery implementation based on cascaded converters can have advantages over traditional centralized battery systems with add-ons active/passive balancing techniques. This paper investigates the use of a modular battery integrated within a cascaded converter and how the choice of the converter topology for the module influences the benefits and limitations of the modular battery system performance. Simulation results have been obtained using detailed battery model to validate the analysis

Next-Generation Battery Management Systems: Dynamic Reconfiguration

Batteries are widely applied to the energy storage and power supply in portable electronics, transportation, power systems, communication networks, etc. They are particularly demanded in the emerging technologies of vehicle electrification and renewable energy integration for a green and sustainable society. To meet various voltage, power, and energy requirements in large-scale applications, multiple battery cells have to be connected in series and/or parallel. While battery technology has advanced significantly in the past decade, existing battery management systems (BMSs) mainly focus on state monitoring and control of battery systems packed in fixed configurations. In fixed configurations, though, the battery system performance is in principle limited by the weakest cells, which can leave large parts severely underutilized. Allowing dynamic reconfiguration of battery cells, on the other hand, allows individual and flexible manipulation of the battery system at cell, module, and pack levels, which may open up a new paradigm for battery management. Following this trend, this paper provides an overview of next-generation BMSs featuring dynamic reconfiguration. Motivated by numerous potential benefits of reconfigurable battery systems (RBSs), the hardware designs, management principles, and optimization algorithms for RBSs are sequentially and systematically discussed. Theoretical and practical challenges during the design and implementation of RBSs are highlighted in the end to stimulate future research and development

Performance Evaluation of Multilevel Converter based Cell Balancer with Reciprocating Air Flow

The modeling and design of an active battery cell balancing system using Multilevel Converter (MLC) for EV/HEV/PHEV is studied under unidirectional as well as reciprocating air flow. The MLC allows to independently switch ON/OFF each battery cell in a battery pack. The optimal policy (OP ) exploiting this extra degree-of-freedom can achieve both temperature and state-of-charge (SoC) balancing among the cells. The OP is calculated as the solution to a convex optimization problem based on the assumption of perfect state information and future driving. This study has shown that OP gives significant benefit in terms of reduction in temperature and SoC deviations, especially under parameter variations, compared to uniformly using all the cells. It is also shown that using reciprocating flow for OP gives no significant benefit. Thus, reciprocating flow is redundant for MLC-based active cell balancing system when operated using OP

On Thermal and State-of-Charge Balancing using Cascaded Multi-level Converters

In this study, the simultaneous use of a multi-level converter (MLC) as a DC-motor drive and as an active battery cell balancer is investigated. MLCs allow each battery cell in a battery pack to be independently switched on and off, thereby enabling the potential non-uniform use of battery cells. By exploiting this property and the brake regeneration phases in the drive cycle, MLCs can balance both the state of charge (SoC) and temperature differences between cells, which are two known causes of battery wear, even without reciprocating the coolant flow inside the pack. The optimal control policy (OP) that considers both battery pack temperature and SoC dynamics is studied in detail based on the assumption that information on the state of each cell, the schedule of reciprocating air flow and the future driving profile are perfectly known. Results show that OP provides significant reductions in temperature and in SoC deviations compared with the uniform use of all cells even with uni-directional coolant flow. Thus, reciprocating coolant flow is a redundant function for a MLC-based cell balancer. A specific contribution of this paper is the derivation of a state-space electro-thermal model of a battery submodule for both uni-directional and reciprocating coolant flows under the switching action of MLC, resulting in OP being derived by the solution of a convex optimization problem

A System Design Approach for Unattended Solar Energy Harvesting Supply

Remote devices, such as sensors and communications devices, require continuously available power. In many applications, conventional approaches are too expensive, too large, or unreliable. For short-term needs, primary batteries may be used. However, they do not scale up well for long-term installations. Instead, energy harvesting methods must be used. Here, a system design approach is introduced that results in a highly reliable, highly available energy harvesting device for remote applications. First, a simulation method that uses climate data and target availability produces Pareto curves for energy storage and generation. This step determines the energy storage requirement in watt-hours and the energy generation requirement in watts. Cost, size, reliability, and longevity requirements are considered to choose particular storage and generation technologies, and then to specify particular components. The overall energy processing system is designed for modularity, fault tolerance, and energy flow control capability. Maximum power point tracking is used to optimize solar panel performance. The result is a highly reliable, highly available power source. Several prototypes have been constructed and tested. Experimental results are shown for one device that uses multicrystalline silicon solar cells and lithium-iron-phosphate batteries to achieve 100% availability. Future designers can use the same approach to design systems for a wide range of power requirements and installation locations