Computer aided solid state battery design method and manufacture of same using selected combinations of characteristics

• US 8,301,285 B2
• Filed: 10/31/2011
• Issued: 10/30/2012
• Est. Priority Date: 10/31/2011
• Status: Active Grant

• Current Assignee: Sakti3, Inc
• Original Assignee: Sakti3, Inc
• Inventors: Zhang, Xiangchun, Chen, Yen-Hung, Wang, Chia-Wei, Sastry, Ann Marie
• Primary Examiner(s): Jarrett, Ryan
• Application Number:
  US13/285,373
• Publication Number:
  US 20120046776A1
• Time in Patent Office: 365 Days
• Field of Search: 700/97, 700/98, 700/17
• US Class Current: 700/97
• CPC Class Codes: H01M 10/052 Li-accumulators
• CPC Class Codes: H01M 10/0562 Solid materials
• CPC Class Codes: H01M 10/0565 Polymeric materials, e.g. gel-type or solid-type
• CPC Class Codes: H01M 10/058 Construction or manufacture
• CPC Class Codes: H01M 4/485 of mixed oxides or hydroxides for inserting or intercalating light metals, e.g. LiTi2O4 or LiTi2OxFy H01M4/505, H01M4/525 take precedence
• CPC Class Codes: H01M 4/525 of mixed oxides or hydroxides containing iron, cobalt or nickel for inserting or intercalating light metals, e.g. LiNiO2, LiCoO2 or LiCoOxFy
• CPC Class Codes: H01M 4/661 Metal or alloys, e.g. alloy coatings H01M4/669 take precedence
• CPC Class Codes: Y02E 60/10 Energy storage using batteries
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries

Abstract

A method of designing and manufacturing a solid-state electrochemical battery cell for a battery device. The method includes building a database of a plurality of first characteristics of a solid-state cells for a battery device and determining at least a third characteristic of the solid-state cell for a given application. The method also includes selecting at least one material of the solid-state electrochemical battery cell, the selected material being from the plurality of first characteristics and forming a plurality of factorial combinations of each component using the selected plurality of first characteristics to derive a respective plurality of solid-state electrochemical battery cells. The method performs a design optimization process for the third characteristic. A step of identifying an optimal design of the second characteristics with the selected first characteristics for each solid-state electrochemical battery cell from the plurality of solid-state cells is included.

Claims

1. A method of designing and manufacturing a solid-state electrochemical cell for a battery device, the method comprising:

building a database of a plurality of first characteristics of the solid-state electrochemical battery cell for a battery device, the database comprising a plurality of second characteristics;

determining at least a third characteristic of the solid-state electrochemical battery cell for a given application;

selecting at least one material of the solid-state electrochemical battery cell, the selected material being from the plurality of first characteristics;

forming a plurality of factorial combinations of a component using the selected plurality of first characteristics to derive a respective plurality of solid state electrochemical battery cells;

performing a design optimization process for the third characteristic;

identifying an optimal design of the plurality of second characteristics with the selected first characteristics for each solid-state electrochemical battery cell from the plurality of solid-state electrochemical battery cells; and

using the optimal design for manufacture of a battery device.

2. The method of claim 1 further outputting a plurality of optimal third characteristics for each solid state electrochemical battery cell and a plurality of optimal second characteristics, and further comprising comparing the optimal third characteristics of each solid-state electrochemical battery cell with the selected first characteristics and the corresponding optimal second characteristics for the given application.

3. The method of claim 1 further comprising ranking a list of combinations of the selected first characteristics and the selected second characteristics for each solid-state electrochemical battery cell based on one or more of the third characteristics.

4. The method of claim 1, wherein the solid-state electrochemical battery cell comprises an anode substrate, an anode current collector, an anode, electrolyte, a cathode, a cathode current collector, and a cathode substrate in sequence.

5. The method of claim 1, wherein the first characteristics of the solid-state electrochemical battery cell comprises a plurality of material types provided for the component, the plurality of material types comprising:

an anode electrode material comprising at least one of a zinc metal, a magnesium metal, a lithium metal (Li), or a lithium intercalation host material which includes a lithium titanium oxide (Li₄Ti₅O₁₂), a graphite (C), or a silicon (Si);

an electrolyte material overlying an anode material comprising at least one of a silver compound, AgI, Ag₂O, Ag₂S, Ag₂Se, P₂O, P₂S, and P₂Se, a lithium solid-electrolyte, lithium phosphorus oxynitride (UPON), Li₃N, Li₁₀GeP₂S₁₂, and Li₂S—

SiS—

Li₃PO₄ a lithium polymer-electrolyte, a lithium salt, LiClO₄/LiPF₆ mixed with a poly-ethylene oxide (PEO), a poly-vinylidene fluoride (PVDF), or a combination of PEO and PVDF;

a cathode electrode material overlying the electrolyte material comprising at least one of Ag₂O, MgMo₆S₈, MgMo₆Se₈, a magnesium intercalatible compound, a lithium intercalation layered metal oxide material, LiCoO₂, LiNiO₂, LiV₂O₅, Li(Ni_xMn_yCo_(1-x-y))O₂, LiNi_xCo_yAl_(1-x-y)O₂ (NCA), LiNi_xMn_yCo_(1-x-y)O₂ (NCM) where (0<

=x<

1, 0<

=y<

1), a spinel material, LiMn₂O₄, LiNi_xMn_2-xO₄ where (0<

=x<

2) an olivine material, LiFePO₄, LiCoPO₄, or LiNiPO₄;

a current collector material comprising at least one of a copper (Cu), an aluminum (Al), a stainless steel, an other conductive metal, or an alloy in the form of a thin foil and bearing;

a separator material overlaying between the anode material and the cathode material, the separator material comprising at least one of a microporous polypropylene/polyethylene membrane; and

a substrate material comprising at least one of a polymer, a metal, or a glass.

6. The method of claim 1, wherein the first characteristics of solid-state electrochemical battery cell further comprise a plurality of material properties of at least one composition in the solid-state electrochemical battery cell, the one component being one of a, mass density, an open circuit potential, an ionic diffusion coefficient, an electrical conductivity, a theoretical capacity, a theoretical volumetric energy density, a theoretical gravimetric energy density, Young'"'"'s modulus, a Poisson'"'"'s ratio, a thermal conductivity, a heat capacity, a thermal expansion coefficient, a maximum state of discharge, or molecular weight.

7. The method of claim 1, wherein the plurality of second characteristics of solid-state electrochemical battery cell comprise at least one of a plurality of physical dimensions, a width, a length, a thickness, a three-dimensional feature of a component, a number of electrochemical cell unit layers, or a porosity.

8. The method of claim 1, wherein the third characteristic of the solid-state electrochemical battery cell comprises a volume, a weight, a capacity, an energy, a power, a gravimetric energy density, a gravimetric power density, a volumetric energy density, a volumetric power density, an output voltage range, a total cost, maximum intercalation induced stresses, and an operational temperature range.

9. The method of claim 1 wherein the given application is selected from one of portable electronics, cell phones, personal digital assistants, music players, tablet computers, video cameras, power tools, power supplies for military use, communications, lighting, imaging, power supplies for aerospace applications, power for satellites, micro air vehicles, power supplies for vehicle applications, hybrid electric vehicles, plug-in hybrid electric vehicles, and fully electric vehicles, the given application further comprising at least one of a fuel cell, an other battery, an IC engine, a combustion device, a capacitor, or a solar cell.

10. The method of claim 1 further comprising a design optimization process, the design optimization process comprising:

specifying design variables of one or more second characteristics for each component of solid-state electrochemical battery cell design;

specifying one or more third characteristics of solid-state electrochemical battery cell as optimization objectives;

sampling plurality of design points in the specified design space for one or more second characteristics for each component of solid-state electrochemical battery cell design with a design of experiment (DOE) approach;

conducting computer simulations of physics models of solid-state electrochemical battery cell on the design points to obtain data sets of optimization objectives of solid-state electrochemical battery cell;

building surrogate models for optimization objectives of solid-state electrochemical battery cell based on the computer simulation or experiment results on design points;

verifying the accuracy of these surrogate models, repeating steps until the accuracy of these surrogate models is less than set criteria; and

identifying an optimal design solution of one or more second characteristics of solid-state electrochemical battery cell by conducting optimization using the surrogate models.

11. The method of claim 10, wherein the design of experiment approach comprises systematically choosing a plurality of design points based on one or more strategies, the one or more strategies being at least one of a Latin hyper cube sampling, a factorial design, a face-centered-central-composite design, or a D-optimal design.

12. The method of claim 10, wherein the conducting computer simulations of physics models of solid-state electrochemical battery cell comprises conducting computer simulations of physics models of solid-state electrochemical battery cell using numerical schema.

13. The method of claim 10, wherein the building surrogate models comprises fitting function at design points.

14. The method of claim 10 wherein the conducting optimization using the surrogate models and the identifying an optimal battery design solution comprises conducting a single or multi-objective optimization process which generates a single optimal solution or a set of optimal solutions.

15. A system for designing a battery device for a given application, the system comprising:

an input and output interface device;

a memory for storing computer readable codes for one or more application modules;

a communication interface device; and

at least one processor coupled to the memory, the input and output interface device, and the communication interface device, the processor being configured to execute the computer readable codes, the computer readable codes including;

a code directed to storing and accessing a material database of design parameters for a battery cell;

a code directed to a battery design process using surrogate models; and

a code directed to processing a candidate material performance against an application specification to determine an anode material, a cathode material, an electrolyte material, a connector material, a current collector material, and a barrier material for the battery device.

16. The system of claim 15 wherein the code directed to a battery design process using surrogate models includes a code directed to conducting computer simulations of physics models of a solid-state electrochemical battery cell, including conducting computer simulations of physics models of the solid-state electrochemical battery cell using numerical schema which include but are not limited to a finite difference method, a finite element method, a finite volume method, and a boundary element method.

17. The system of claim 15 wherein the code directed to a battery design process using surrogate models includes a code directed to fitting functions at design points, where the fitting functions include but are not limited to polynomial responses, a kriging model, a radial basis neural network, and support vector machines.

18. The system of claim 15 wherein the code directed to processing a candidate material performance against an application specification includes a code directed to conducting the single or multi-objective optimization process which generates a single optimal solution or a set of optimal solutions.