Linear parameter varying model predictive control for engine assemblies
US-10060373-B2 · Aug 28, 2018 · US
US10787944B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10787944-B2 |
| Application number | US-201816174748-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 30, 2018 |
| Priority date | Oct 30, 2017 |
| Publication date | Sep 29, 2020 |
| Grant date | Sep 29, 2020 |
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A method for simultaneous optimization of nitrogen oxide emissions and carbon dioxide emissions of a combustion engine with an exhaust gas aftertreatment system of a motor vehicle. The method comprises the following steps: at the start a prediction horizon (PH) is selected (100), then a nitrogen oxide limit value (mNOx_max) is specified (101). Minimisation (102) of a cost function (K) comprising the nitrogen oxide emissions and the carbon dioxide emissions is carried out, wherein the nitrogen oxide limit value (mNOx_max) is complied with. Then actuators of the combustion engine are set (105) to a setpoint value (S) that is determined when minimizing (102) the cost function (K). Finally, the steps of the method are repeated.
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The invention claimed is: 1. A method for simultaneous optimization of nitrogen oxide emissions and carbon dioxide emissions of a combustion engine ( 2 ) with an exhaust gas aftertreatment system ( 10 ) of a motor vehicle comprising the following steps: Selecting ( 100 ), via a computer, a prediction horizon (PH, PH 1 , PH 2 ); Specifying ( 101 ), via a computer, a nitrogen oxide limit value (m NOx_max ); Minimizing ( 102 ), via a computer, a cost function (K) comprising the nitrogen oxide emissions and the carbon dioxide emissions, wherein the nitrogen oxide limit value (m NOx_max ) is complied with, and wherein a violation of the nitrogen oxide limit value (m NOx_max ) is taken into account in the form of a penalty term (Θ) in the cost function (K) that adopts a first value if the nitrogen oxide limit value (m NOx_max ) is not exceeded and adopts a second value of finite size if the nitrogen oxide limit value (m NOx_max ) is exceeded; and Adjusting ( 105 ) actuators of the combustion engine ( 2 ) to a setpoint value (S) determined when minimizing ( 102 ) the cost function (K). 2. The method according to claim 1 , wherein models ( 200 - 208 ) of the route to be controlled are incorporated in the minimization ( 102 ) of the cost function (K). 3. The method according to claim 1 , wherein a weighting factor (Ψ) is used in order to vary a weighting between the nitrogen oxide raw emissions and the carbon dioxide emissions. 4. The method according to claim 3 , wherein during the minimization ( 102 ) of the cost function (K) a weighting factor (Ψ) is determined that is used when adjusting ( 105 ) the actuators of the combustion engine ( 2 ). 5. The method according to claim 1 , wherein during the minimization ( 102 ) of the cost function (K) a correction factor (f NSC ) for adjustment of the regeneration strategy for a nitrogen oxide storage catalytic converter ( 11 ) is determined that is used when adjusting ( 105 ) the actuators of the combustion engine ( 2 ). 6. The method according to claim 1 , wherein during the minimization ( 102 ) of the cost function (K) a heating strategy for the catalytic converters ( 11 , 12 , 13 ) is determined that is used when adjusting ( 105 ) the actuators of the combustion engine ( 2 ). 7. The method according to claim 1 , wherein the minimization ( 102 ) of the cost function (K) is carried out using at least one selected from the group consisting of a policy iteration, a value iteration, dynamic programming, a rollout algorithm, a shooting method. 8. The method according to claim 1 , wherein the prediction horizon (PH 1 ) is based on a specifiable period of time. 9. The method according to claim 1 , wherein a prediction horizon (PH 2 ) is based on a specifiable length of a route. 10. The method according to claim 9 , wherein the route-based prediction horizon (PH 2 ) is converted into a period of time by using the average speed of the motor vehicle and/or by using a speed to be expected over the route. 11. The method according to claim 1 , wherein from a plurality of prediction horizons (PH 1 , PH 2 ) the prediction horizon is selected that ends furthest into the future. 12. A non-transitory, computer-readable medium comprising a computer program that, when executed by an electronic control unit, causes the electronic control unit to select a prediction horizon (PH, PH 1 , PH 2 ); specify a nitrogen oxide limit value (m NOx_max ); minimize a cost function (K) comprising the nitrogen oxide emissions and the carbon dioxide emissions, wherein the nitrogen oxide limit value (m NOx_max ) is complied with, and wherein a violation of the nitrogen oxide limit value (m NOx_max ) is taken into account in the form of a penalty term (Θ) in the cost function (K) that adopts a first value if the nitrogen oxide limit value (m NOx_max ) is not exceeded and adopts a second value of finite size if the nitrogen oxide limit value (m NOx_max ) is exceeded; and adjust actuators of the combustion engine ( 2 ) to a setpoint value (S) determined when minimizing ( 102 ) the cost function (K). 13. An electronic control unit ( 3 ) configured to select a prediction horizon (PH, PH 1 , PH 2 ), specify a nitrogen oxide limit value (m NOx_max ); minimize a cost function (K) comprising the nitrogen oxide emissions and the carbon dioxide emissions, wherein the nitrogen oxide limit value (m NOx_max ) is complied with, and wherein a violation of the nitrogen oxide limit value (m NOx_max ) is taken into account in the form of a penalty term (Θ) in the cost function (K) that adopts a first value if the nitrogen oxide limit value (m NOx_max ) is not exceeded and adopts a second value of finite size if the nitrogen oxide limit value (m NOx_max ) is exceeded; and adjust actuators of the combustion engine ( 2 ) to a setpoint value (S) determined when minimizing ( 102 ) the cost function (K).
Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters · CPC title
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