US2014039682A1PendingUtilityA1
Nonlinear model predictive control of a biofuel fermentation process
Assignee: ROCKWELL AUTOMATION TECH INCPriority: Oct 31, 2006Filed: Oct 8, 2013Published: Feb 6, 2014
Est. expiryOct 31, 2026(~0.2 yrs left)· nominal 20-yr term from priority
C12P 7/06Y02E50/10C12M 41/12C12M 41/46C12M 41/48G05B 13/048C12M 45/09C12M 41/44G05B 13/04
56
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Claims
Abstract
A system and method are provided for managing batch fermentation in a biofuel production process. A nonlinear control model of yeast growth and fermentable sugar concentration for biofuel (e.g., fuel ethanol) production in a batch fermentation process (pure and/or fed-batch fermentation) of a biofuel production process is provided. Process information for the batch fermentation process is received, and the nonlinear control model executed using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process, e.g., fermentation temperature and/or enzyme flow, for substantially maximizing yeast growth and achieving target fermentable sugar concentrations. The batch fermentation process is then controlled in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, where substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.
Claims
exact text as granted — not AI-modified1 . A method for managing a batch fermentation process in a biofuel production process, comprising:
providing a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process, wherein yeast growth is based on a theoretical maximum yeast growth rate as a function of temperature, the fermentable sugar concentration, a biofuel concentration, a fermentable sugar saturation constant, a biofuel saturation constant, and a yeast death rate as a function of temperature; receiving process information for the batch fermentation process; executing the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and controlling the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.
2 . The method of claim 1 , wherein the one or more fermentation process variables comprise one or more of:
fermentation temperature; or enzyme flow, comprising a rate of enzyme flow to the fermentation process, wherein the enzyme operates to convert starches to fermentable sugar.
3 . The method of claim 1 ,
wherein the nonlinear control model comprises a physics-based model including equations for a volumetric change in a fermentation tank, a yeast activation rate, a yeast growth rate, the yeast death rate, a fermentable sugar conversion rate, a dextrin conversion rate, a biofuel production rate, and an enzyme addition rate.
4 . The method of claim 1 , further comprising:
specifying an objective function, wherein the object function specifies: said substantially maximizing yeast growth; and the target fermentable sugar concentrations; wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises: an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.
5 . The method of claim 1 , wherein the process information comprises one or more of:
measured attributes of the batch fermentation process; laboratory data; or predicted values for unmeasured attributes of the batch fermentation process computed by one or more predictive models
6 . The method of claim 1 ,
wherein the nonlinear control model of yeast growth and fermentable sugar concentration comprises: a nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration; and a nonlinear control model of temperature and enzyme concentration as a function of fermenter cooler return temperature and enzyme flow.
7 . The method of claim 6 , wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises:
executing the nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration using the process information as input to determine values of temperature and enzyme concentration for the batch fermentation process that substantially maximize yeast growth and achieve the target fermentable sugar concentration; and executing the nonlinear control model of temperature and enzyme concentration using the process information as input to determine the values for fermenter cooler return temperature and enzyme flow for achieving the determined values of temperature and enzyme concentration in the batch fermentation process.
8 . The method of claim 1 , wherein the batch fermentation process comprises a fed-batch process.
9 . The method of claim 1 , wherein the batch fermentation process comprises a pure batch process.
10 . The method of claim 1 , further comprising:
performing said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.
11 . The method of claim 1 ,
wherein the biofuel comprises ethanol, and wherein yeast growth is based on the following equation:
yeast
growth
_
=
(
μ
x
max
(
T
)
y
sugar
(
k
x
1
+
y
EtOH
)
(
k
x
2
+
y
sugar
)
-
r
d
(
t
)
)
_
where μ x max (T) is the theoretical maximum yeast growth rate as a function of temperature T, y sugar is the fermentable sugar concentration, y EtOH is an ethanol concentration, k x1 is an ethanol saturation constant, k x2 is the fermentable sugar saturation constant, and r d (T) is the yeast death rate as a function of temperature T.
12 . A computer-accessible memory medium configured for managing a batch fermentation process in a biofuel production process, wherein the memory medium stores:
a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process, wherein yeast growth is based on a theoretical maximum yeast growth rate as a function of temperature, the fermentable sugar concentration, a biofuel concentration, a fermentable sugar saturation constant, a biofuel saturation constant, and a yeast death rate as a function of temperature; and program instructions, executable to perform: receiving process information for the batch fermentation process; executing the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and controlling the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.
13 . The memory medium of claim 12 , wherein the one or more fermentation process variables comprise one or more of:
fermentation temperature; or enzyme flow, comprising a rate of enzyme flow to the fermentation process, wherein the enzyme operates to convert starches to fermentable sugar.
14 . The memory medium of claim 12 ,
wherein the nonlinear control model comprises a physics-based model including equations for a volumetric change in a fermentation tank, a yeast activation rate, a yeast growth rate, the yeast death rate, a fermentable sugar conversion rate, a dextrin conversion rate, a biofuel production rate, and an enzyme addition rate.
15 . The memory medium of claim 12 , wherein the program instructions are further executable to perform:
receiving an objective function, wherein the object function specifies: said substantially maximizing yeast growth; and the target fermentable sugar concentrations; wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises: an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.
16 . The memory medium of claim 12 , wherein the process information comprises one or more of:
measured attributes of the batch fermentation process; laboratory data; or predicted values for unmeasured attributes of the batch fermentation process computed by one or more predictive models.
17 . The memory medium of claim 12 , wherein the nonlinear control model of yeast growth and fermentable sugar concentration comprises:
a nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration; and a nonlinear control model of temperature and enzyme concentration as a function of fermenter cooler return temperature and enzyme flow.
18 . The memory medium of claim 17 , wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises:
executing the nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration using the process information as input to determine values of temperature and enzyme concentration for the batch fermentation process that substantially maximize yeast growth and achieve the target fermentable sugar concentration; and executing the nonlinear control model of temperature and enzyme concentration using the process information as input to determine the values for fermenter cooler return temperature and enzyme flow for achieving the determined values of temperature and enzyme concentration in the batch fermentation process.
19 . The memory medium of claim 12 , wherein the batch fermentation process comprises a fed-batch process.
20 . The memory medium of claim 12 , wherein the batch fermentation process comprises a pure batch process.
21 . The memory medium of claim 12 , wherein the program instructions are further executable to perform:
performing said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.
22 . The memory medium of claim 12 ,
wherein the biofuel comprises ethanol, and wherein yeast growth is based on the following equation:
yeast
growth
_
=
(
μ
x
max
(
T
)
y
sugar
(
k
x
1
+
y
EtOH
)
(
k
x
2
+
y
sugar
)
-
r
d
(
t
)
)
_
where μ x max (T) is the theoretical maximum yeast growth rate as a function of temperature T, y sugar is the fermentable sugar concentration, y EtOH is an ethanol concentration, k x1 is an ethanol saturation constant, k x2 is the fermentable sugar saturation constant, and r d (T) is the yeast death rate as a function of temperature T.
23 . A system for managing a batch fermentation process in a biofuel production process, comprising:
a processor; and a memory medium coupled to the processor, wherein the memory medium stores: a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process, wherein yeast growth is based on a theoretical maximum yeast growth rate as a function of temperature, the fermentable sugar concentration, a biofuel concentration, a fermentable sugar saturation constant, a biofuel saturation constant, and a yeast death rate as a function of temperature; and program instructions, executable by the processor to:
receive process information for the batch fermentation process;
execute the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and
control the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.
24 . The system of claim 23 , wherein the program instructions are further executable to:
receive an objective function, wherein the object function specifies:
said substantially maximizing yeast growth; and
the target fermentable sugar concentrations;
wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises:
an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.
25 . The system of claim 23 , wherein the program instructions are further executable to:
perform said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.Join the waitlist — get patent alerts
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