Parallel Battery Pack Control Using SOH and SOC Power Allocation
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Solution Overview
Problem
Renewable energy sources like solar and wind power lack flexibility in meeting changing energy demands due to their inability to be dispatched on demand, necessitating energy storage systems that can store and release electricity as needed.
Innovation Solution
A distributed power energy storage system (DPESS) utilizing multi-source inputs smart technology (MIST) with heterogeneous battery packs, including new and second-use electric vehicle batteries, connected in parallel and managed by a controller that monitors and controls state of health and state of charge to optimize charge/discharge rates, eliminating the need for pre-selection and series connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If renewable energy sources (solar and wind power) are used for energy generation, then clean and renewable energy supply is improved, but flexibility in meeting changing energy demands deteriorates due to inability to be dispatched on demand
Solution Approach 1:
The system segments the energy storage into multiple independent battery packs (first battery pack, second battery pack, etc.) connected in parallel, each with its own BPMU for independent monitoring and control. This segmentation allows flexible dispatch of individual packs to meet changing energy demands while maintaining overall system functionality.
Solution Approach 2:
The controller dynamically adjusts the charge/discharge rates of individual battery packs based on real-time SOH and SOC data, enabling the system to adapt flexibly to changing energy demands. The dynamic control allows the system to dispatch energy from specific packs based on their current state, resolving the contradiction between renewable energy supply and dispatchability.
2Ease of manufacture
If heterogeneous battery packs (new and second-use EV batteries) are connected in parallel without pre-selection, then ease of manufacture and system flexibility are improved, but manufacturing precision and system reliability deteriorate due to varying battery conditions
Solution Approach 1:
Each battery pack is equipped with a BPMU that continuously monitors SOH and SOC and provides feedback to the controller. The controller uses this feedback information to intelligently allocate charge/discharge tasks to appropriate packs, ensuring system reliability despite heterogeneity. This feedback mechanism allows the system to accommodate mixed battery types without compromising reliability.
Solution Approach 2:
The system changes the operational parameters (charge/discharge rates) of individual battery packs based on their specific SOH and SOC states. By dynamically adjusting these parameters, the system can safely utilize heterogeneous battery packs with different capacities and health levels, resolving the contradiction between ease of manufacture and system reliability.
3Adaptability or versatility
If individual power converters are assigned to each battery pack, then adaptability and control precision are improved, but device complexity increases
Solution Approach 1:
The power converters are designed as universal units that can work with any battery pack type. Each converter serves multiple functions: power conversion, bidirectional communication with BPMU, and participation in coordinated control. This multi-functionality reduces the need for specialized components, managing system complexity while maintaining adaptability.
Solution Approach 2:
The BPMU acts as an intermediary between the battery packs and the controller, managing communication and control signals. This intermediary layer simplifies the overall system architecture by standardizing interfaces, allowing individual power converters to be assigned to battery packs without creating unmanageable complexity.
4Reliability
If the controller monitors and controls SOH and SOC of each battery pack in real-time, then reliability and safety are improved, but use of energy and computational resources increase
Solution Approach 1:
The controller implements partial monitoring by focusing on critical parameters (SOH and SOC) rather than all possible battery parameters. This selective monitoring approach maintains reliability and safety while minimizing the energy and computational resources required for the monitoring function.
Solution Approach 2:
The BPMU in each battery pack performs self-monitoring of SOH and SOC and autonomously communicates this data to the controller. This self-service approach reduces the burden on the main controller, lowering its energy consumption and computational load while maintaining real-time monitoring capability for system reliability.
Data Source
AI summary
An electrical energy storage system, a controller, and methods of using the same are provided. The system includes battery packs connected in parallel, one or more battery power management unit, one or more power converters, and a controller. The controller includes one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to perform steps for discharging or charging. The steps include: reading data including state of health (SOH) and state of charge (SOC) from each battery pack, connecting a respective battery pack with a respective power converter; receiving a power command from an energy management system, calculating a respective power rate of each battery pack based on the data of SOH, SOC, and the power command, and discharging power from battery packs to a grid or charging power to battery packs based on the power rate of each battery pack.