Hybrid Battery Output Estimation via Multi-Parameter Relational Equations
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Solution Overview
Problem
Accurately estimating the maximum output of a battery in hybrid electric vehicles is challenging due to the dynamic behavior of the battery's charged state, temperature, and discharge capacity, which affects the battery's efficiency and increases the risk of over-charge or over-discharge.
Innovation Solution
A method that calculates the interrelation between the battery's maximum output and its charged state, temperature, and discharge capacity using specific relational equations to estimate the battery's maximum output, compensating for degradation, and transmits this information to a control unit to manage charge/discharge operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cell voltage is measured to check SOC, then measurement is simple, but voltage decreases suddenly during rapid acceleration irrespective of actual SOC leading to inaccurate estimation
Solution Approach 1:
The patent segments the battery characteristics into multiple dimensions: open circuit voltage characteristics, internal resistance characteristics, and capacity characteristics. By measuring multiple parameters (voltage, current, temperature) and analyzing them separately through different relational equations, the system achieves accurate SOC estimation without relying solely on terminal voltage, thus resolving the contradiction between measurement simplicity and accuracy.
2Measurement precision
If discharge capacity is measured to check SOC, then accurate measurement is possible under constant conditions, but available capacity varies with load conditions making the algorithm very complex
Solution Approach 1:
The patent changes the parameters used for SOC estimation from direct capacity measurement under varying load conditions to a combination of open circuit voltage, internal resistance, and temperature parameters. By establishing relational equations that account for temperature and charge/discharge rate effects on these parameters, the system achieves accurate SOC estimation with a manageable algorithm complexity.
3Device complexity
If maximum output is estimated without considering temperature and degradation, then estimation is simple, but accuracy is insufficient due to dynamic behavior of charged state and temperature
Solution Approach 1:
The patent introduces dynamic adjustment mechanisms by establishing relational equations that account for temperature variations and charge/discharge rate effects. The maximum output estimation is continuously adjusted based on real-time temperature and SOC data, allowing the system to adapt to changing operating conditions while maintaining reasonable computational complexity.
Data Source
AI summary
Disclosed is a method of estimating a maximum output of a battery for a hybrid electric vehicle (HEV). The method comprises extracting maximum charge/discharge outputs of the battery depending on a plurality of charged states (SOC) of the battery under which the vehicle is able to be driven and calculating an interrelation between them; extracting maximum charge/discharge outputs of the battery at plural temperatures under which the vehicle is able to be driven, and calculating an interrelation between them; extracting degradations of outputs of the battery as a capacity of the battery is discharged during the traveling, and calculating an interrelation between them; and based on the interrelations obtained, estimating a maximum output of the battery using a function.